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Internet Research Task Force (IRTF) K. Pentikousis, Ed.
Request for Comments: 7476 EICT
Category: Informational B. Ohlman
ISSN: 2070-1721 Ericsson
D. Corujo
Universidade de Aveiro
G. Boggia
Politecnico di Bari
G. Tyson
Queen Mary, University of London
E. Davies
Trinity College Dublin
A. Molinaro
UNIRC
S. Eum
NICT
March 2015
Information-Centric Networking: Baseline Scenarios
Abstract
This document aims at establishing a common understanding about a set
of scenarios that can be used as a base for the evaluation of
different information-centric networking (ICN) approaches so that
they can be tested and compared against each other while showcasing
their own advantages. Towards this end, we review the ICN literature
and document scenarios which have been considered in previous
performance evaluation studies. We discuss a variety of aspects that
an ICN solution can address. This includes general aspects, such as,
network efficiency, reduced complexity, increased scalability and
reliability, mobility support, multicast and caching performance,
real-time communication efficiency, energy consumption frugality, and
disruption and delay tolerance. We detail ICN-specific aspects as
well, such as information security and trust, persistence,
availability, provenance, and location independence.
This document is a product of the IRTF Information-Centric Networking
Research Group (ICNRG).
Pentikousis, et al. Informational [Page 1]
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Status of This Memo
This document is not an Internet Standards Track specification; it is
published for informational purposes.
This document is a product of the Internet Research Task Force
(IRTF). The IRTF publishes the results of Internet-related research
and development activities. These results might not be suitable for
deployment. This RFC represents the consensus of the Information-
Centric Networking Research Group of the Internet Research Task Force
(IRTF). Documents approved for publication by the IRSG are not a
candidate for any level of Internet Standard; see Section 2 of RFC
5741.
Information about the current status of this document, any errata,
and how to provide feedback on it may be obtained at
http://www.rfc-editor.org/info/rfc7476.
Copyright Notice
Copyright (c) 2015 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents
(http://trustee.ietf.org/license-info) in effect on the date of
publication of this document. Please review these documents
carefully, as they describe your rights and restrictions with respect
to this document.
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Table of Contents
1. Introduction ....................................................3
1.1. Baseline Scenario Selection ................................4
1.2. Document Goals and Outline .................................5
2. Scenarios .......................................................6
2.1. Social Networking ..........................................6
2.2. Real-Time Communication ....................................7
2.3. Mobile Networking ..........................................9
2.4. Infrastructure Sharing ....................................11
2.5. Content Dissemination .....................................13
2.6. Vehicular Networking ......................................14
2.7. Delay- and Disruption-Tolerance ...........................17
2.7.1. Opportunistic Content Sharing ......................20
2.7.2. Emergency Support and Disaster Recovery ............21
2.8. Internet of Things ........................................22
2.9. Smart City ................................................25
3. Cross-Scenario Considerations ..................................27
3.1. Multiply Connected Nodes and Economics ....................27
3.2. Energy Efficiency .........................................31
3.3. Operation across Multiple Network Paradigms ...............33
4. Summary ........................................................34
5. Security Considerations ........................................35
6. Informative References .........................................36
Acknowledgments ...................................................44
Authors' Addresses ................................................44
1. Introduction
Information-centric networking (ICN) marks a fundamental shift in
communications and networking. In contrast with the omnipresent and
very successful host-centric paradigm, which is based on perpetual
connectivity and the end-to-end principle, ICN changes the focal
point of the network architecture from the end host to "named
information" (or content, or data). In this paradigm, connectivity
may well be intermittent. End-host and in-network storage can be
capitalized upon transparently, as bits in the network and on storage
devices have exactly the same value. Mobility and multiaccess are
the norm, and anycast, multicast, and broadcast are natively
supported.
It is also worth noting that with the transition from a host-centric
to an information-centric communication model the security paradigm
changes as well. In a host-centric network, the basic idea is to
create secure (remote-access) tunnels to trusted providers of data.
In an information-centric network, on the other hand, any source
(cache) should be equally usable. This requires some mechanism for
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making each information item trustworthy by itself; this can be
achieved, for example, by name-data integrity or by signing data
objects.
Although interest in ICN is growing rapidly, ongoing work on
different architectures, such as NetInf [NetInf], the original
Content-Centric Networking [CCN], and its successors, Project CCNx
[CCNx] and Named Data Networking (NDN) [NDNP], the Publish-Subscribe
Internet (PSI) architecture [PSI], and the Data-Oriented Network
Architecture [DONA] is far from being completed. One could think of
ICN today as being at a stage of development similar to that of
packet-switched networking in the late 1970s when different
technologies, e.g., DECnet, Internetwork Packet Exchange (IPX), and
IP, just to name a few, were being actively developed and put to the
test. As such, ICN's current development phase and the plethora of
approaches to tackle the hardest problems make this a very active and
growing research area, but, on the downside, it also makes it more
difficult to compare different proposals on an equal footing. This
document aims to partially address this by establishing a common
understanding about potential experimental setups where different ICN
approaches can be tested and compared against each other while
showcasing their advantages.
The first draft version of this document appeared in November 2012.
It was adopted by ICNRG at IETF 87 (July 2013) as the document to
address the work item on the definition of "reference baseline
scenarios to enable performance comparisons between different
approaches". Earlier draft versions of this document have been
presented during the ICNRG meetings at IETF 85, IETF 86, IETF 87,
IETF 88, IETF 89, and the ICNRG interim meeting in Stockholm in
February 2013. This document has been reviewed, commented, and
discussed extensively for a period of nearly two years by the vast
majority of ICNRG members, which certainly exceeds 100 individuals.
It is the consensus of ICNRG that the baseline scenarios described in
this document should be published in the IRTF Stream of the RFC
series. This document does not constitute a standard.
1.1. Baseline Scenario Selection
Earlier surveys [SoA1] [SoA2] note that describing ICN architectures
is akin to shooting a moving target. We find that comparing these
different approaches is often even more tricky. It is not uncommon
that researchers devise different performance evaluation scenarios,
typically with good reason, in order to highlight the advantages of
their approach. This should be expected to some degree at this early
stage of ICN development. Nevertheless, this document shows that
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certain baseline scenarios seem to emerge in which ICN architectures
could showcase their comparative advantages over current systems, in
general, and against each other, in particular.
This document surveys the peer-reviewed ICN literature and presents
prominent evaluation study cases as a foundation for the baseline
scenarios to be considered by the IRTF Information-Centric Networking
Research Group (ICNRG) in its future work. There are two goals for
this document: first, to provide a set of use cases and applications
that highlight opportunities for testing different ICN proposals;
second, to identify key attributes of a common set of techniques that
can be instrumental in evaluating ICN. Further, these scenarios are
intended to equip researchers with sufficient configuration data to
effectively evaluate their ICN proposals in a variety of settings,
particularly extending beyond scenarios focusing simply on
traditional content delivery. The overall aim is that each scenario
is described at a sufficient level of detail, and with adequate
references to already published work, so that it can serve as the
base for comparative evaluations of different approaches. Example
code that implements some of the scenarios and topologies included in
this document is available from
<http://telematics.poliba.it/icn-baseline-scenarios>.
1.2. Document Goals and Outline
This document incorporates input from ICNRG participants and their
corresponding text contributions, has been reviewed by several ICNRG
active participants (see Section 7), and represents the consensus of
the research group. However, this document does not constitute an
IETF standard, but is an Informational document; see also [RFC5743].
As mentioned above, these scenarios are intended to provide a
framework for evaluating different ICN approaches. The methodology
for how to do these evaluations as well as definitions of metrics
that should be used are described in a separate document
[EVAL-METHOD]. In addition, interested readers should consider
reviewing [CHALLENGES].
The remainder of this document presents a number of scenarios grouped
into several categories in Section 2, followed by a number of cross-
scenario considerations in Section 3. Overall, note that certain
evaluation scenarios span across these categories, so the boundaries
between them should not be considered rigid and inflexible.
Section 4 summarizes the main evaluation aspects across the range of
scenarios discussed in this document.
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2. Scenarios
This section presents nine scenario categories based on use cases and
evaluations that have appeared in the peer-reviewed literature.
2.1. Social Networking
Social-networking applications have proliferated over the past decade
based on overlay content dissemination systems that require large
infrastructure investments to roll out and maintain. Content
dissemination is at the heart of the ICN paradigm. Therefore, we
would expect that social-networking scenarios are a "natural fit" for
comparing ICN performance with traditional client-server TCP/IP-based
systems. Mathieu et al. [ICN-SN], for instance, illustrate how an
Internet Service Provider (ISP) can capitalize on CCN to deploy a
short-message service akin to Twitter at a fraction of the complexity
of today's systems. Their key observation is that such a service can
be seen as a combination of multicast delivery and caching. That is,
a single user addresses a large number of recipients, some of which
receive the new message immediately as they are online at that
instant, while others receive the message whenever they connect to
the network.
Along similar lines, Kim et al. [VPC] present an ICN-based social-
networking platform in which a user shares content with her/his
family and friends without the need for centralized content servers;
see also Section 2.4, below, and [CBIS]. Based on the CCN naming
scheme, [VPC] takes a user name to represent a set of devices that
belong to the person. Other users in this in-network, serverless
social sharing scenario can access the user's content not via a
device name/address but with the user's name. In [VPC], signature
verification does not require any centralized authentication server.
Kim and Lee [VPC2] present a proof-of-concept evaluation in which
users with ordinary smartphones can browse a list of members or
content using a name, and download the content selected from the
list.
In other words, the above-mentioned evaluation studies indicate that
with ICN there may be no need for an end-to-end system design that
intermediates between content providers and consumers in a hub-and-
spoke fashion at all times.
Earlier work by Arianfar et al. [CCR] considers a similar pull-based
content retrieval scenario using a different architecture, pointing
to significant performance advantages. Although the authors consider
a network topology (redrawn in Figure 1 for convenience) that has
certain interesting characteristics, they do not explicitly address
social networking in their evaluation scenario. Nonetheless,
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similarities are easy to spot: "followers" (such as C0, C1, ..., and
Cz in Figure 1) obtain content put "on the network" (I1, ..., Im, and
B1, B2) by a single user (e.g., Px) relying solely on network
primitives.
\--/
|C0|
/--\ +--+ +--+ +--+ +--+
*=== |I0| === |I1| ... |In| |P0|
\--/ +--+ +--+ +--+ +--+
|C1| \ / o
/--\ +--+ +--+ o
o |B1| === |B2| o
o o o o o +--+ +--+ o
o / \ o
o +--+ +--+ +--+ +--+
o *=== |Ik| === |Il| ... |Im| |Px|
\--/ +--+ +--+ +--+ +--+
|Cz|
/--\
Figure 1. Dumbbell with Linear Daisy Chains
In summary, the social-networking scenario aims to exercise each ICN
architecture in terms of network efficiency, multicast support,
caching performance and its reliance on centralized mechanisms (or
lack thereof).
2.2. Real-Time Communication
Real-time audio and video (A/V) communications include an array of
services ranging from one-to-one voice calls to multiparty multimedia
conferences with support ranging from whiteboards to augmented
reality. Real-time communications have been studied and deployed in
the context of packet- and circuit-switched networks for decades.
The stringent Quality of Service (QoS) requirements that this type of
communication imposes on network infrastructure are well known.
Since one could argue that network primitives that are excellent for
information dissemination are not well-suited for conversational
services, ICN evaluation studies should consider real-time
communication scenarios in detail.
Notably, Jacobson et al. [VoCCN] presented an early evaluation where
the performance of a VoIP (Voice over IP) call using an information-
centric approach was compared with that of an off-the-shelf VoIP
implementation using RTP/UDP. The results indicated that despite the
extra cost of adding security support in the ICN approach,
performance was virtually identical in the two cases evaluated in
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their testbed. However, the experimental setup presented is quite
rudimentary, while the evaluation considered a single voice call
only. Xuan and Yan [NDNpb] revisit the same scenario but are
primarily interested in reducing the overhead that may arise in one-
to-one communication employing an ICN architecture. Both studies
illustrate that quality telephony services are feasible with at least
one ICN approach. That said, future ICN evaluations should employ
standardized call arrival patterns, for example, following well-
established methodologies from the QoS and QoE (Quality of
Experience) evaluation toolbox and would need to consider more
comprehensive metrics.
Given the widespread deployment of real-time A/V communications, an
evaluation of an ICN system should demonstrate capabilities beyond
feasibility. For example, with respect to multimedia conferencing,
Zhu et al. [ACT] describe the design of a distributed audio
conference tool based on NDN. Their system includes ICN-based
conference discovery, speaker discovery, and voice data distribution.
The reported evaluation results point to gains in scalability and
security. Moreover, Chen et al. [G-COPSS] explore the feasibility of
implementing a Massively Multiplayer Online Role-Playing Game
(MMORPG) based on CCNx code and show that stringent temporal
requirements can be met, while scalability is significantly improved
when compared to a host-centric (IP-based) client-server system.
This type of work points to benefits for both the data and control
path of a modern network infrastructure.
Real-time communication also brings up the issue of named data
granularity for dynamically generated content. In many cases, A/V
data is generated in real-time and is distributed immediately. One
possibility is to apply a single name to the entire content, but this
could result in significant distribution delays. Alternatively,
distributing A/V content in smaller "chunks" that are named
individually may be a better option with respect to real-time
distribution but raises naming scalability concerns.
We observe that, all in all, the ICN research community has hitherto
only scratched the surface of illustrating the benefits of adopting
an information-centric approach as opposed to a host-centric one, and
thus more work is recommended in this direction. Scenarios in this
category should illustrate not only feasibility but reduced
complexity, increased scalability, reliability, and capacity to meet
stringent QoS/QoE requirements when compared to established host-
centric solutions. Accordingly, the primary aim of this scenario is
to exercise each ICN architecture in terms of its ability to satisfy
real-time QoS requirements and provide improved user experience.
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2.3. Mobile Networking
IP mobility management relies on anchors to provide ubiquitous
connectivity to end-hosts as well as moving networks [MMIN]. This is
a natural choice for a host-centric paradigm that requires end-to-end
connectivity and a continuous network presence for hosts [SCES]. An
implicit assumption in host-centric mobility management is therefore
that the mobile node aims to connect to a particular peer, as well as
to maintain global reachability and service continuity [EEMN].
However, with ICN, new ideas about mobility management should come to
the fore, capitalizing on the different nature of the paradigm, such
as native support for multihoming, abstraction of network addresses
from applications, less dependence on connection-oriented sessions,
and so on [MOBSURV].
Dannewitz et al. [N-Scen] illustrate a scenario where a multiaccess
end-host can retrieve email securely using a combination of cellular
and Wireless Local Area Network (WLAN) connectivity. This scenario
borrows elements from previous work, e.g., [DTI], and develops them
further with respect to multiaccess. Unfortunately, Dannewitz et al.
[N-Scen] do not present any results demonstrating that an ICN
approach is, indeed, better. That said, the scenario is interesting
as it considers content specific to a single user (i.e., her mailbox)
and does point to reduced complexity. It is also compatible with
recent work in the Distributed Mobility Management (DMM) Working
Group within the IETF. Finally, Xylomenos et al. [PSIMob] as well as
Pentikousis [EEMN] argue that an information-centric architecture can
avoid the complexity of having to manage tunnels to maintain end-to-
end connectivity as is the case with mobile anchor-based protocols
such as Mobile IP (and its variants). Similar considerations hold
for a vehicular (networking) environment, as we discuss in Section
2.6.
Overall, mobile networking scenarios have not been developed in
detail, let alone evaluated at a large scale. Further, the majority
of scenarios discussed so far have related to the mobility of the
information consumer, rather than the source. We expect that in the
coming period more papers will address this topic. Earlier work
[mNetInf] argues that for mobile and multiaccess networking scenarios
we need to go beyond the current mobility management mechanisms in
order to capitalize on the core ICN features. They present a testbed
setup (redrawn in Figure 2) that can serve as the basis for other ICN
evaluations. In this scenario, node "C0" has multiple network
interfaces that can access local domains N0 and N1 simultaneously,
allowing C0 to retrieve objects from whichever server (I2 or I3) can
supply them without necessarily needing to access the servers in the
core network "C" (P1 and P2). Lindgren [HybICN] explores this
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scenario further for an urban setting. He uses simulation and
reports sizable gains in terms of reduction of object retrieval times
and core network capacity use.
+------------+ +-----------+
| Network N0 | | Network C |
| | | |
| +--+ | ==== | +--+ |
| |I2| | | |P1| |
| +--+ | | +--+ |
| \--/ | | |
+-----|C0|---+ | |
| /--\ | | |
| +--+ | | |
| |I3| | | +--+ |
| +--+ | ==== | |P2| |
| | | +--+ |
| Network N1 | | |
+------------+ +-----------+
Figure 2. Overlapping Wireless Multiaccess
The benefits from capitalizing on the broadcast nature of wireless
access technologies has yet to be explored to its full potential in
the ICN literature, including quantifying possible gains in terms of
energy efficiency [E-CHANET]. Obviously, ICN architectures must
avoid broadcast storms. Early work in this area considers
distributed packet suppression techniques that exploit delayed
transmissions and overhearing; examples can be found in [MobiA] and
[CCNMANET] for ICN-based mobile ad-hoc networks (MANETs), and in
[RTIND] and [CCNVANET] for vehicular scenarios.
One would expect that mobile networking scenarios will be naturally
coupled with those discussed in the previous sections, as more users
access social-networking and multimedia applications through mobile
devices. Further, the constraints of real-time A/V applications
create interesting challenges in handling mobility, particularly in
terms of maintaining service continuity. This scenario therefore
spans across most of the others considered in this document with the
likely need for some level of integration, particularly considering
the well-documented increases in mobile traffic. Mobility is further
considered in Section 2.7 and the economic consequences of nodes
having multiple network interfaces is explored in Section 3.1.
Host-centric mobility management has traditionally used a range of
metrics for evaluating performance on a per-node and network-wide
level. The first metric that comes to mind is handover latency,
defined in [RFC5568] as the "period during which the mobile node is
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unable to send or receive packets". This metric should be considered
in ICN performance evaluation studies dealing with mobility. Note
that, in IP-based networks, handover latency has been addressed by
the introduction of mobility management protocols that aim to hide
node mobility from the correspondent node, and often follow a make-
before-break approach in order to ensure seamless connectivity and
minimize (or eliminate altogether) handover latency. The "always-on"
and "always best connected" [ABC] paradigms have guided mobility
management research and standardization for a good decade or so. One
can argue that such mechanisms are not particularly suited for ICN.
That said, there has been a lot of interest recently in distributed
mobility management schemes (see [MMIN] for a summary), where
mobility management support is not "always on" by default. Such
schemes may be more suitable for ICN. As a general recommendation,
ICN designs should aim to minimize handover latency so that the end-
user and service QoE is not affected adversely.
Network overhead, such as the amount of signaling necessary to
minimize handover latency, is also a metric that should be considered
when studying ICN mobility management. In the past, network overhead
has been seen as one of the main factors hindering the deployment of
various mobility solutions. In IP-based networks, network overhead
includes, but is not limited to, tunneling overhead, in-band control
protocol overhead, mobile terminal and network equipment state
maintenance and update. ICN designs and evaluation studies should
clearly identify the network overhead associated with handling
mobility. Alongside network overhead, deployment complexity should
also be studied.
To summarize, mobile networking scenarios should aim to provide
service continuity for those applications that require it, decrease
complexity and control signaling for the network infrastructure, as
well as increase wireless capacity utilization by taking advantage of
the broadcast nature of the medium. Beyond this, mobile networking
scenarios should form a cross-scenario platform that can highlight
how other scenarios can still maintain their respective performance
metrics during periods of high mobility.
2.4. Infrastructure Sharing
A key idea in ICN is that the network should secure information
objects per se, not the communications channel that they are
delivered over. This means that hosts attached to an information-
centric network can share resources on an unprecedented scale,
especially when compared to what is possible in an IP network. All
devices with network access and storage capacity can contribute their
resources thereby increasing the value of an information-centric
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network, although compensation schemes motivating users to contribute
resources remain a research challenge primarily from a business
perspective.
For example, Jacobson et al. [CBIS] argue that in ICN the "where and
how" of obtaining information are new degrees of freedom. They
illustrate this with a scenario involving a photo-sharing application
that takes advantage of whichever access network connectivity is
available at the moment (WLAN, Bluetooth, and even SMS) without
requiring a centralized infrastructure to synchronize between
numerous devices. It is important to highlight that since the focus
of communication changes, keep-alives in this scenario are simply
unnecessary, as devices participating in the testbed network
contribute resources in order to maintain user content consistency,
not link state information as is the case in the host-centric
paradigm. This means that the notion of "infrastructure" may be
completely different in the future.
Muscariello et al. [SHARE], for instance, presented early work on an
analytical framework that attempts to capture the storage/bandwidth
tradeoffs that ICN enables and can be used as the foundation for a
network planning tool. In addition, Chai et al. [CL4M] explore the
benefits of ubiquitous caching throughout an information-centric
network and argue that "caching less can actually achieve more."
These papers also sit alongside a variety of other studies that look
at various scenarios such as caching HTTP-like traffic [CCNCT] and
BitTorrent-like traffic [BTCACHE]. We observe that much more work is
needed in order to understand how to make optimal use of all
resources available in an information-centric network. In real-world
deployments, policy and commercial considerations are also likely to
affect the use of particular resources, and more work is expected in
this direction as well.
In conclusion, scenarios in this category would cover the
communication-computation-storage tradeoffs that an ICN deployment
must consider. This would exercise features relating to network
planning, perhaps capitalizing on user-provided resources, as well as
operational and economical aspects of ICN, and contrast them with
other approaches. An obvious baseline to compare against in this
regard is existing federations of IP-based Content Distribution
Networks (CDNs), such as the ones discussed in the IETF Content
Delivery Networks Interconnection Working Group.
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2.5. Content Dissemination
Content dissemination has attracted more attention than other aspects
of ICN. Scenarios in this category abound in the literature,
including stored and streaming A/V distribution, file distribution,
mirroring and bulk transfers, versioned content services (cf.
Subversion-type revision control), as well as traffic aggregation.
Decentralized content dissemination with on-the-fly aggregation of
information sources was envisaged in [N-Scen], where information
objects can be dynamically assembled based on hierarchically
structured subcomponents. For example, a video stream could be
associated with different audio streams and subtitle sets, which can
all be obtained from different sources. Using the topology depicted
in Figure 1 as an example, an application at C1 may end up obtaining,
say, the video content from I1, but the user-selected subtitles from
Px. Semantics and content negotiation, on behalf of the user, were
also considered, e.g., for the case of popular tunes that may be
available in different encoding formats. Effectively, this scenario
has the information consumer issuing independent requests for content
based on information identifiers, and stitching the pieces together
irrespective of "where" or "how" they were obtained.
A case in point for content dissemination are vehicular ad hoc
networks (VANETs), as an ICN approach may address their needs for
information dissemination between vehicles better than today's
solutions, as discussed in the following section. The critical part
of information dissemination in a VANET scenario revolves around
"where" and "when". For instance, one may be interested in traffic
conditions 2 km ahead while having no interest in similar information
about the area around the path origin. VANET scenarios may provide
fertile ground for showcasing the ICN advantage with respect to
content dissemination especially when compared with current host-
centric approaches. That said, information integrity and filtering
are challenges that must be addressed. As mentioned above, content
dissemination scenarios in VANETs have a particular affinity to the
mobility scenarios discussed in Section 2.3.
Content dissemination scenarios, in general, have a large overlap
with those described in the previous sections and are explored in
several papers, such as [DONA], [PSI], [PSIMob], [NetInf], [CCN],
[CBIS], and [CCR], just to name a few. In addition, Chai et al.
[CURLING] present a hop-by-hop hierarchical content resolution
approach that employs receiver-driven multicast over multiple
domains, advocating another content dissemination approach. Yet,
largely, work in this area did not address the issue of access
authorization in detail. Often, the distributed content is mostly
assumed to be freely accessible by any consumer. Distribution of
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paid-for or otherwise restricted content on a public ICN network
requires more attention in the future. Fotiou et al. [ACDICN]
consider a scheme to this effect, but it still requires access to an
authorization server to verify the user's status after the
(encrypted) content has been obtained. This may effectively negate
the advantage of obtaining the content from any node, especially in a
disruption-prone or mobile network.
In summary, scenarios in this category aim to exercise primarily
scalability and the cost and performance attributes of content
dissemination. Particularly, they should highlight the ability of an
ICN to scale to billions of objects, while not exceeding the cost of
existing content dissemination solutions (i.e., CDNs) and, ideally,
increasing performance. These should be shown in a holistic manner,
improving content dissemination for both information consumers and
publishers of all sizes. We expect that in particular for content
dissemination, in both extreme as well as typical scenarios, can be
specified by drawing data from current CDN deployments.
2.6. Vehicular Networking
Users "on wheels" are interested in road safety, traffic efficiency,
and infotainment applications that can be supported through vehicle-
to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless
communications. These applications exhibit unique features in terms
of traffic generation patterns, delivery requirements, and spatial
and temporal scope, which pose great challenges to traditional
networking solutions. VANETs, by their nature, are characterized by
challenges such as fast-changing topology, intermittent connectivity,
and high node mobility, but also by the opportunity to combine
information from different sources as each vehicle does not care
about "who" delivers the named data objects.
ICN is an attractive candidate solution for vehicular networking, as
it has several advantages. First, ICN fits well to the nature of
typical vehicular applications that are geography- and time-dependent
(e.g., road traveler information, accident warning, point-of-interest
advertisements) and usually target vehicles in a given area,
regardless of their identity or IP address. These applications are
likely to benefit from in-network and decentralized data caching and
replication mechanisms. Second, content caching is particularly
beneficial for intermittent on-the-road connectivity and can speed up
data retrieval through content replication in several nodes. Caching
can usually be implemented at relatively low cost in vehicles, as the
energy demands of the ICN device are likely to be a negligible
fraction of the total vehicle energy consumption, thus allowing for
sophisticated processing, continuous communication, and adequate
storage in the vehicle. Finally, ICN natively supports asynchronous
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data exchange between end-nodes. By using (and redistributing)
cached named information objects, a mobile node can serve as a link
between disconnected areas. In short, ICN can enable communication
even under intermittent network connectivity, which is typical of
vehicular environments with sparse roadside infrastructure and fast-
moving nodes.
The advantages of ICN in vehicular networks were preliminarily
discussed in [EWC] and [DMND], and additionally investigated in
[DNV2V], [RTIND], [CCNHV], [CCDIVN], [CCNVANET], and [CRoWN]. For
example, Bai and Krishnamachari [EWC] take advantage of the localized
and dynamic nature of a VANET to explore how a road congestion
notification application can be implemented. Wang et al. [DMND]
consider data collection where Road-Side Units (RSUs) collect
information from vehicles by broadcasting NDN-like Interest packets.
The proposed architecture is evaluated using simulation in a grid
topology and is compared against a host-centric alternative based on
Mobile IP. See Figure 3 for an indicative example of an urban VANET
topology. Their results indicate high efficiency for ICN even at
high speeds. That said, this work is a preliminary exploration of
ICN in vehicular environments, so various issues remain for
evaluation. They include system scalability to large numbers of
vehicles and the impact of vehicles that forward Interest packets or
relay data to other vehicles.
+ - - _- - -_- - - -_- - _- - - +
| /_\ /_\ /_\ /_\ |
| o o o o o o o o |
| +-------+ +-------+ _ |
| | | | |/_\ |
| _ | | | |o o |
| /_\| | | | |
| o o+--_----+\===/+--_----+ |
| /_\ |RSU| /_\ |
| o o /===\ o o |
| +-------+ +-------+ _ |
| | | | |/_\ |
| _ | | | |o o |
|/_\ | | | | |
|o o +_-----_+ +_-----_+ |
| /_\ /_\ /_\ /_\ |
+_ _ o_o_ _o_o_ _ _o_o_ _o_o_ _ +
Figure 3. Urban Grid VANET Topology
As mentioned in the previous section, due to the short communication
duration between a vehicle and the RSU, and the typically short time
of sustained connectivity between vehicles, VANETs may be a good
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showcase for the ICN advantages with respect to content
dissemination. Wang et al. [DNV2V], for instance, analyze the
advantages of hierarchical naming for vehicular traffic information
dissemination. Arnould et al. [CCNHV] apply ICN principles to safety
information dissemination between vehicles with multiple radio
interfaces. In [CCDIVN], TalebiFard and Leung use network coding
techniques to improve content dissemination over multiple ICN paths.
Amadeo et al. [CCNVANET] [CRoWN] propose an application-independent
ICN framework for content retrieval and distribution where the role
of provider can be played equivalently by both vehicles and RSUs.
ICN forwarding is extended through path-state information carried in
Interest and Data packets, stored in a new data structure kept by
vehicular nodes, and exploited also to cope with node mobility.
Typical scenarios for testing content distribution in VANETs may be
highways with vehicles moving in straight lines, with or without RSUs
along the road, as shown in Figure 4. With an NDN approach in mind,
for example, RSUs may send Interest packets to collect data from
vehicles [DMND], or vehicles may send Interest packets to collect
data from other peers [RTIND] or from RSUs [CCNVANET]. Figure 2
applies to content dissemination in VANET scenarios as well, where C0
represents a vehicle that can obtain named information objects via
multiple wireless peers and/or RSUs (I2 and I3 in the figure). Grid
topologies such as the one illustrated in Figure 3 should be
considered in urban scenarios with RSUs at the crossroads or
co-located with traffic lights as in [CRoWN].
\___/ \___/
|RSU| |RSU|
================================
_ _ _ _
/_\ /_\ /_\ /_\
_ _ o_o_ _o_o_ _o_o_ _o_o_ _ _ _
_ _ _ _
/_\ /_\ /_\ /_\
o o o o o o o o
================================
Figure 4. Highway VANET Topology
To summarize, VANET scenarios aim to exercise ICN deployment from
various perspectives, including scalability, caching, transport, and
mobility issues. There is a need for further investigation in (i)
challenging scenarios (e.g., disconnected segments); (ii) scenarios
involving both consumer and provider mobility; (iii) smart caching
techniques that take into consideration node mobility patterns,
spatial and temporal relevance, content popularity, and social
relationships between users/vehicles; (iv) identification of new
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applications (beyond data dissemination and traffic monitoring) that
could benefit from the adoption of an ICN paradigm in vehicular
networks (e.g., mobile cloud, social networking).
2.7. Delay- and Disruption-Tolerance
Delay- and Disruption-Tolerant Networking (DTN) originated as a means
to extend the Internet to interplanetary communications [DTN].
However, it was subsequently found to be an appropriate architecture
for many terrestrial situations as well. Typically, this was where
delays were greater than protocols such as TCP could handle, and
where disruptions to communications were the norm rather than
occasional annoyances, e.g., where an end-to-end path does not
necessarily exist when communication is initiated. DTN has now been
applied to many situations, including opportunistic content sharing,
handling infrastructural issues during emergency situations (e.g.,
earthquakes) and providing connectivity to remote rural areas without
existing Internet provision and little or no communications or power
infrastructure.
The DTN architecture [RFC4838] is based on a "store, carry, and
forward" paradigm that has been applied extensively to situations
where data is carried between network nodes by a "data mule", which
carries bundles of data stored in some convenient storage medium
(e.g., a USB memory stick). With the advent of sensor and peer-to-
peer (P2P) networks between mobile nodes, DTN is becoming a more
commonplace type of networking than originally envisioned. Since ICN
also does not rely on the familiar end-to-end communications
paradigm, there are clear synergies [DTNICN]. It could therefore be
argued that many of the key principles embodied within DTN also exist
in ICN, as we explain next.
First, both approaches rely on in-network storage. In the case of
DTN, bundles are stored temporarily on devices on a hop-by-hop basis.
In the case of ICN, information objects are also cached on devices in
a similar fashion. As such, both paradigms must provision storage
within the network.
Second, both approaches espouse late binding of names to locations
due to the potentially large interval between request and response
generation. In the case of DTN, it is often impossible to predict
the exact location (in a disconnected topology) where a node will be
found. Similarly, in the case of ICN, it is also often impossible to
predict where an information object might be found. As such, the
binding of a request/bundle to a destination (or routing locator)
must be performed as late as possible.
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Finally, both approaches treat data as a long-lived component that
can exist in the network for extended periods of time. In the case
of DTN, bundles are carried by nodes until appropriate next hops are
discovered. In the case of ICN, information objects are typically
cached until storage is exhausted. As such, both paradigms require a
direct shift in the way applications interact with the network.
Through these similarities, it becomes possible to identify many DTN
principles that are already in existence within ICN architectures.
For example, ICN nodes will often retain information objects locally,
making them accessible later on, much as DTN bundles are handled.
Consequently, these synergies suggest strong potential for marrying
the two technologies. This could include, for instance, building new
integrated Information-Centric Delay Tolerant Network (ICDTN)
protocols or, alternatively, building ICN schemes over existing DTN
protocols (and vice versa).
The above similarities suggest that integration of the two principles
would be feasible. Beyond this, there are also a number of
identifiable direct benefits. Through caching and replication, ICN
offers strong information resilience, whilst, through store-and-
forward, DTN offers strong connectivity resilience. As such, both
architectures could benefit greatly from each other. Initial steps
have already been taken in the DTN community to integrate ICN
principles, e.g., the Bundle Protocol Query Block [BPQ] has been
proposed for the DTN Bundle Protocol [RFC5050]. Similarly, initial
steps have also been taken in the ICN community, such as [SLINKY].
In fact, the Scalable and Adaptive Internet Solutions (SAIL) project
has developed a prototype implementation of NetInf running over the
DTN Bundle Protocol.
Of course, in many circumstances, information-centricity is not
appropriate for use in delay- and disruption-tolerant environments.
This is particularly the case when information is not the key
communications atom transmitted. Further, situations where a single
sink is always used for receiving information may not warrant the
identification and routing of independent information objects.
However, there are a number of key scenarios where clear benefits
could be gained by introducing information-centric principles into
DTNs, two of which we describe later in this section.
For the purpose of evaluating the use of ICNs in a DTN setting, two
key scenarios are identified in this document. (Note the rest of
this section uses the term "ICDTN".) These are both prominent use
cases that are currently active in both the ICN and DTN communities.
The first is opportunistic content sharing, whilst the second is the
use of ad hoc networks during disaster recovery (e.g., earthquakes).
We discuss both types of scenarios in the context of a simulation-
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based evaluation: due to the scale and mobility of DTN-like setups,
this is the primary method of evaluation used. Within the DTN
community, the majority of simulations are performed using the
Opportunistic Network Environment (ONE) simulator [ONE], which is
referred to in this document. Before exploring the two scenarios,
the key shared components of their simulation are discussed. This is
separated into the two primary inputs that are required: the
environment and the workload.
In both types of scenarios the environment can be abstractly modeled
by a time series of active connections between device pairs. Unlike
other scenarios in this document, an ICDTN scenario therefore does
not depend on (relatively) static topologies but, rather, a set of
time-varying disconnected topologies. In opportunistic networks,
these topologies are actually products of the mobility of users. For
example, if two users walk past each other, an opportunistic link can
be created. There are two methods used to generate these mobility
patterns and, in turn, the time series of topologies. The first is
synthetic, whereby a (mathematical) model of user behavior is created
in an agent-based fashion, e.g., random waypoint, Gauss-Markov. The
second is trace-driven, whereby the mobility of real users is
recorded and used. In both cases, the output is a sequence of time-
stamped "contacts", i.e., periods of time in which two devices can
communicate. An important factor missing from typical mobility
traces, however, is the capacity of these contacts: how much data can
be transferred? In both approaches to modeling mobility, links are
usually configured as Bluetooth or Wi-Fi (ONE easily allows this,
although lower-layer considerations are ignored, e.g., interference).
This is motivated by the predominance of these technologies on mobile
phones.
The workload in an ICDTN is modeled much like the workload within the
other scenarios. It involves object creation/placement and object
retrieval. Object creation/placement can either be done statically
at the beginning of the simulations or, alternatively, dynamically
based on a model of user behavior. In both cases, the latter is
focused on, as it models far better the characteristics of the
scenarios.
Once the environment and workload have been configured, the next step
is to decide the key metrics for the study. Unlike traditional
networking, the QoS expectation is typically far lower in an ICDTN,
thereby moving away from metrics such as throughput. At a high
level, it is of clear interest to evaluate different ICN approaches
with respect to both their delay- and disruption-tolerance (i.e., how
effective is the approach when used in an environment subject to
significant delay and/or disruption) and to their active support for
operations in a DTN environment.
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The two most prominent metrics considered in a host-centric DTN are
delivery probability and delivery delay. The former relates to the
probability by which a sent message will be received within a certain
delay bound, whilst the latter captures the average length of time it
takes for nodes to receive the message. These metrics are similarly
important in an ICDTN, although they are slightly different due to
the request-response nature of ICN. Therefore, the two most
prominent evaluative metrics are satisfaction probability and
satisfaction delay. The former refers to the probability by which an
information request (e.g., Interest) will be satisfied (i.e., how
often a Data response will be received). Satisfaction delay refers
to the length of time it takes an information request to be
satisfied.
Note that the key difference between the host-centric and
information-centric metrics is the need for a round-trip rather than
a one-way communication. Beyond this, depending on the focus of the
work, other elements that may be investigated include name
resolution, routing, and forwarding in disconnected parts of the
network; support for unidirectional links; number of round trips
needed to complete a data transfer; long-term content availability
(or resilience); efficiency in the face of disruption; and so on. It
is also important to weigh these performance metrics against the
necessary overheads. In the case of an ICDTN, this is generally
measured by the number of message replicas required to access
content. Note that routing in a DTN is often replication based,
which leads to many copies of the same message.
2.7.1. Opportunistic Content Sharing
The first key baseline scenario in this context is opportunistic
content sharing. This occurs when mobile nodes create opportunistic
links between each other to share content of interest. For example,
people riding on an underground train can pass news items between
their mobile phones. Equally, content generated on the phones (e.g.,
tweets [TWIMIGHT]) could be stored for later forwarding (or even
forwarded amongst interested passengers on the train). Such
scenarios, clearly, must be based around either the altruistic or
incentivized interaction amongst users. The latter is a particularly
active area of research. These networks are often termed "pocket-
switched networks", as they are independently formed between the user
devices. Here, the evaluative scenario of ICDTN microblogging is
proposed. As previously discussed, the construction of such an
evaluative scenario requires a formalization of its environment and
workload. Fortunately, there exist a number of datasets that offer
exactly this information required for microblogging.
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In terms of the environment (i.e., mobility patterns), the Haggle
project produced contact traces based on conference attendees using
Bluetooth. These traces are best targeted at application scenarios
in which a small group of (50-100) people are in a relatively
confined space. In contrast, larger-scale traces are also available,
most notably MIT's Reality Mining project. These are better suited
for cases where longer-term movement patterns are of interest.
The second input, workload, relates to the creation and consumption
of microblogs (e.g., tweets). This can be effectively captured
because subscriptions conveniently formalize who consumes what. For
bespoke purposes, specific data can be directly collected from
Twitter for trace-driven simulations. Several Twitter datasets are
already available to the community containing a variety of data,
ranging from Tweets to follower graphs. See
<http://www.tweetarchivist.com> and
<http://socialcomputing.asu.edu/datasets/Twitter>. These datasets
can therefore be used to extract information production, placement,
and consumption.
2.7.2. Emergency Support and Disaster Recovery
The second key baseline scenario in this context relates to the use
of ICDTNs in emergency scenarios. In these situations, it is typical
for infrastructure to be damaged or destroyed, leading to the
collapse of traditional forms of communications (e.g., cellular
telephone networks). This has been seen in the recent North Indian
flooding, as well as the 2011 Tohoku earthquake and tsunami. Power
problems often exacerbate the issue, with communication failures
lasting for days. Therefore, in order to address this, DTNs have
been used due to their high levels of resilience and independence
from fixed infrastructure. The most prominent use of DTNs in
disaster areas would be the dissemination of information, e.g.,
warnings and evacuation maps. Unlike the previous scenario, it can
be assumed that certain users (e.g., emergency responders) are highly
altruistic. However, it is likely many other users (e.g., endangered
civilians) might become far more conservative in how they use their
devices for battery-conserving purposes. Here, we focus on the
dissemination of standard broadcast information that should be
received by all parties; generally, this is something led by
emergency responders.
For the environmental setup, there are no commonly used mobility
traces for disaster zones, unlike in the previous scenario. This is
clearly due to the difficultly (near impossibility) of acquiring them
in a real setting. That said, various synthetic models are
available. The Post-Disaster Mobility Model [MODEL1] models
civilians and emergency responders after a disaster has occurred,
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with people attempting to reach evacuation points (this has also been
implemented in the ONE simulator). Aschenbruck et al. [MODEL2] focus
on emergency responders, featuring the removal of nodes from the
disaster zone, as well as things like obstacles (e.g., collapsed
buildings). Cabrero et al. [MODEL3] also look at emergency
responders but focus on patterns associated with common procedures.
For example, command and control centers are typically set up with
emergency responders periodically returning. Clearly, the mobility
of emergency responders is particularly important in this setting
because they usually are the ones who will "carry" information into
the disaster zone. It is recommended that one of these emergency-
specific models be used during any evaluations, due to the inaccuracy
of alternate models used for "normal" behavior.
The workload input in this evaluative scenario is far simpler than
for the previous scenario. In emergency cases, the dissemination of
individual pieces of information to all parties is the norm. This is
often embodied using things like the Common Alert Protocol (CAP),
which is an XML standard for describing warning message. It is
currently used by various systems, including the Integrated Public
Alert & Warning System and Google Crisis Response. As such, small
objects (e.g., 512 KB to 2 MB) are usually generated containing text
and images; note that the ONE simulator offers utilities to easily
generate these. These messages are also always generated by central
authorities, therefore making the placement problem easier (they
would be centrally generated and given to emergency responders to
disseminate as they pass through the disaster zone). The key
variable is therefore the generation rate, which is synonymous with
the rate that microblogs are written in the previous scenario. This
will largely be based on the type of disaster occurring; however,
hourly updates would be an appropriate configuration. Higher rates
can also be tested, based on the rate at which situations change
(landslides, for example, can exhibit highly dynamic properties).
To summarize, this section has highlighted the applicability of ICN
principles to existing DTN scenarios. Two evaluative setups have
been described in detail, namely, mobile opportunistic content
sharing (microblogging) and emergency information dissemination.
2.8. Internet of Things
Advances in electronics miniaturization combined with low-power
wireless access technologies (e.g., ZigBee, Near Field Communication
(NFC), Bluetooth, and others) have enabled the coupling of
interconnected digital services with everyday objects. As devices
with sensors and actuators connect into the network, they become
"smart objects" and form the foundation for the so-called Internet of
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Things (IoT). IoT is expected to increase significantly the amount
of content carried by the network due to machine-to-machine (M2M)
communication as well as novel user-interaction possibilities.
Yet, the full potential of IoT does not lie in simple remote access
to smart object data. Instead, it is the intersection of Internet
services with the physical world that will bring about the most
dramatic changes. Burke [IoTEx], for instance, makes a very good
case for creating everyday experiences using interconnected things
through participatory sensing applications. In this case, inherent
ICN capabilities for data discovery, caching, and trusted
communication are leveraged to obtain sensor information and enable
content exchange between mobile users, repositories, and
applications.
Kutscher and Farrell [IWMT] discuss the benefits that ICN can provide
in these environments in terms of naming, caching, and optimized
transport. The Named Information URI scheme (ni) [RFC6920], for
instance, could be used for globally unique smart object
identification, although an actual implementation report is not
currently available. Access to information generated by smart
objects can be of varied nature and often vital for the correct
operation of large systems. As such, supporting timestamping,
security, scalability, and flexibility need to be taken into account.
Ghodsi et al. [NCOA] examine hierarchical and self-certifying naming
schemes and point out that ensuring reliable and secure content
naming and retrieval may pose stringent requirements (e.g., the
necessity for employing PKI), which can be too demanding for low-
powered nodes, such as sensors. That said, earlier work by Heidemann
et al. [nWSN] shows that, for dense sensor network deployments,
disassociating sensor naming from network topology and using named
content at the lowest level of communication in combination with in-
network processing of sensor data is feasible in practice and can be
more efficient than employing a host-centric binding between node
locator and the content existing therein.
Burke et al. [NDNl] describe the implementation of a building
automation system for lighting control where the security, naming,
and device discovery NDN mechanisms are leveraged to provide
configuration, installation, and management of residential and
industrial lighting control systems. The goal is an inherently
resilient system, where even smartphones can be used for control.
Naming reflects fixtures with evolved identification and node-
reaching capabilities, thus simplifying bootstrapping, discovery, and
user interaction with nodes. The authors report that this ICN-based
system requires less maintenance and troubleshooting than typical
IP-based alternatives.
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Biswas et al. [CIBUS] visualize ICN as a contextualized information-
centric bus (CIBUS) over which diverse sets of service producers and
consumers coexist with different requirements. ICN is leveraged to
unify different platforms to serve consumer-producer interaction in
both infrastructure and ad hoc settings. Ravindran et al. [Homenet]
show the application of this idea in the context of a home network,
where consumers (residents) require policy-driven interactions with
diverse services such as climate control, surveillance systems, and
entertainment systems. Name-based protocols are developed to enable
zero-configuration node and service discovery, contextual service
publishing and subscription, policy-based routing and forwarding with
name-based firewall, and hoc device-to-device communication.
IoT exposes ICN concepts to a stringent set of requirements that are
exacerbated by the quantity of nodes, as well as by the type and
volume of information that must be handled. A way to address this is
proposed in [IoTScope], which tackles the problem of mapping named
information to an object, diverting from the currently typical
centralized discovery of services and leveraging the intrinsic ICN
scalability capabilities for naming. It extends the base [PURSUIT]
design with hierarchically based scopes, facilitating lookup, access,
and modifications of only the part of the object information that the
user is interested in. Another important aspect is how to
efficiently address resolution and location of the information
objects, particularly when large numbers of nodes are connected, as
in IoT deployments. In [ICN-DHT], Katsaros et al. propose a
Distributed Hash Table (DHT) that is compared with the Data-Oriented
Network Architecture described in [DONA]. Their results show how
topological routing information has a positive impact on resolution,
at the expense of memory and processing overhead.
The use of ICN mechanisms in IoT scenarios faces the most dynamic and
heterogeneous type of challenges, when taking into consideration the
requirements and objectives of such integration. The disparity in
technologies (not only in access technologies, but also in terms of
end-node diversity such as sensors, actuators, and their
characteristics) as well as in the information that is generated and
consumed in such scenarios, will undoubtedly bring about many of the
considerations presented in the previous sections. For instance, IoT
shares similarities with the constraints and requirements applicable
to vehicular networking. Here, a central problem is the deployment
of mechanisms that can use opportunistic connectivity in unreliable
networking environments (similar to the vehicular networking and DTN
scenarios).
However, one important concern in IoT scenarios, also motivated by
this strongly heterogeneous environment, is how content dissemination
will be affected by the different semantics of the disparate
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information and content being shared. In fact, this is already a
difficult problem that goes beyond the scope of ICN [SEMANT]. With
the ability of the network nodes to cache forwarded information to
improve future requests, a challenge arises regarding whether the ICN
fabric should be involved in any kind of procedure (e.g., tagging)
that facilitates the relationship or the interpretation of the
different sources of information.
Another issue lies with the need for having energy-efficiency
mechanisms related to the networking capabilities of IoT
infrastructures. Often, the devices in IoT deployments have limited
battery capabilities, and thus need low power consumption schemes
working at multiple levels. In principle, energy efficiency gains
should be observed from the inherent in-network caching capability.
However, this might not be the most usual case in IoT scenarios,
where the information (particularly from sensors or controlling
actuators) is more akin to real-time traffic, thus reducing the scale
of potential savings due to ubiquitous in-network caching.
ICN approaches, therefore, should be evaluated with respect to their
capacity to handle the content produced and consumed by extremely
large numbers of diverse devices. IoT scenarios aim to exercise ICN
deployment from different aspects, including ICN node design
requirements, efficient naming, transport, and caching of time-
restricted data. Scalability is particularly important in this
regard as the successful deployment of IoT principles could increase
both device and content numbers dramatically beyond all current
expectations.
2.9. Smart City
The rapid increase in urbanization sets the stage for the most
compelling and challenging environments for networking. By 2050 the
global population will reach nine billion people, 75% of which will
dwell in urban areas. In order to cope with this influx, many cities
around the world have started their transformation toward the "smart
city" vision. Smart cities will be based on the following innovation
axes: smart mobility, smart environment, smart people, smart living,
and smart governance. In development terms, the core goal of a smart
city is to become a business-competitive and attractive environment,
while serving citizen well-being [CPG].
In a smart city, ICT plays a leading role and acts as the glue
bringing together all actors, services, resources (and their
interrelationships) that the urban environment is willing to host and
provide [MVM]. ICN appears particularly suitable for these
scenarios. Domains of interest include intelligent transportation
systems, energy networks, health care, A/V communications, peer-to-
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peer and collaborative platforms for citizens, social inclusion,
active participation in public life, e-government, safety and
security, and sensor networks. Clearly, this scenario has close ties
to the vision of IoT, discussed in the previous section, as well as
to vehicular networking.
Nevertheless, the road to build a real information-centric digital
ecosystem will be long, and more coordinated effort is required to
drive innovation in this domain. We argue that smart-city needs and
ICN technologies can trigger a virtuous innovation cycle toward
future ICT platforms. Recent concrete ICN-based contributions have
been formulated for home energy management [iHEMS], geo-localized
services [ACC], smart-city services [IB], and traffic information
dissemination in vehicular scenarios [RTIND]. Some of the proposed
ICN-based solutions are implemented in real testbeds, while others
are evaluated through simulation.
Zhang et al. [iHEMS] propose a secure publish-subscribe architecture
for handling the communication requirements of Home Energy Management
Systems (HEMS). The objective is to safely and effectively collect
measurement and status information from household elements, aggregate
and analyze the data, and ultimately enable intelligent control
decisions for actuation. They consider a simple experimental testbed
for their proof-of-concept evaluation, exploiting open source code
for the ICN implementation, and emulating some node functionality in
order to facilitate system operation.
A different scenario is considered in [ACC], where DHTs are employed
for distributed, scalable, and geographically aware service lookup in
a smart city. Also in this case, the ICN application is validated by
considering a small-scale testbed: a small number of nodes are
emulated with simple embedded PCs or specific hardware boards (e.g.,
for some sensor nodes); other nodes (which connect the principal
actors of the tests) are emulated with workstations. The proposal in
[IB] draws from a smart-city scenario (mainly oriented towards waste
collection management) comprising sensors and moving vehicles, as
well as a cloud-computing system that supports data retrieval and
storage operations. The main aspects of this proposal are analyzed
via simulation using open source code that is publicly available.
Some software applications are designed on real systems (e.g., PCs
and smartphones).
With respect to evaluating ICN approaches in smart-city scenarios, it
is necessary to consider generic metrics useful to track and monitor
progress on services results and also for comparing localities
between themselves and learn from the best [ISODIS]. In particular,
it is possible to select a specific set of Key Performance Indicators
(KPIs) for a given project in order to evaluate its success. These
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KPIs may reflect the city's environmental and social goals, as well
as its economic objectives, and they can be calculated at the global,
regional, national, and local levels. Therefore, it is not possible
to define a unique set of interesting metrics, but in the context of
smart cities, the KPIs should be characterized with respect to the
developed set of services offered by using the ICN paradigm.
To sum up, smart-city scenarios aim to exercise several ICN aspects
in an urban environment. In particular, they can be useful to (i)
analyze the capacity of using ICN for managing extremely large data
sets; (ii) study ICN performance in terms of scalability in
distributed services; (iii) verify the feasibility of ICN in a very
complex application like vehicular communication systems; and (iv)
examine the possible drawbacks related to privacy and security issues
in complex networked environments.
3. Cross-Scenario Considerations
This section discusses considerations that span multiple scenarios.
3.1. Multiply Connected Nodes and Economics
The evolution of, in particular, wireless networking technologies has
resulted in a convergence of the bandwidth and capabilities of
various different types of network. Today, a leading-edge mobile
telephone or tablet computer will typically be able to access a Wi-Fi
access point, a 4G cellular network, and the latest generation of
Bluetooth local networking. Until recently, a node would usually
have a clear favorite network technology appropriate to any given
environment. The choice would, for example, be primarily determined
by the available bandwidth with cost as a secondary determinant.
Furthermore, it is normally the case that a device only uses one of
the technologies at a time for any particular application.
It seems likely that this situation will change so that nodes are
able to use all of the available technologies in parallel. This will
be further encouraged by the development of new capabilities in
cellular networks including Small Cell Networks [SCN] and
Heterogeneous Networks [HetNet]. Consequently, mobile devices will
have similar choices to wired nodes attached to multiple service
providers allowing "multihoming" via the various different
infrastructure networks as well as potential direct access to other
mobile nodes via Bluetooth or a more capable form of ad hoc Wi-Fi.
Infrastructure networks are generally under the control of separate
economic entities that may have different policies about the
information of an ICN deployed within their network caches. As ICN
shifts the focus from nodes to information objects, the interaction
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between networks will likely evolve to capitalize on data location
independence, efficient and scalable in-network named object
availability, and access via multiple paths. These interactions
become critical in evaluating the technical and economic impact of
ICN architectural choices, as noted in [ArgICN]. Beyond simply
adding diversity in deployment options, these networks have the
potential to alter the incentives among existing (and future, we may
add) network players, as noted in [EconICN].
Moreover, such networks enable more numerous internetwork
relationships where exchange of information may be conditioned on a
set of multilateral policies. For example, shared SCNs are emerging
as a cost-effective way to address coverage of complex environments
such as sports stadiums, large office buildings, malls, etc. Such
networks are likely to be a complex mix of different cellular and
WLAN access technologies (such as HSPA, LTE, and Wi-Fi) as well as
ownership models. It is reasonable to assume that access to content
generated in such networks may depend on contextual information such
as the subscription type, timing, and location of both the owner and
requester of the content. The availability of such contextual
information across diverse networks can lead to network
inefficiencies unless data management can benefit from an
information-centric approach. The "Event with Large Crowds"
demonstrator created by the SAIL project investigated this kind of
scenario; more details are available in [SAIL-B3].
Jacobson et al. [CCN] include interactions between networks in their
overall system design and mention both "an edge-driven, bottom-up
incentive structure" and techniques based on evolutions of existing
mechanisms both for ICN router discovery by the end-user and for
interconnecting between Autonomous Systems (ASes). For example, a
BGP extension for domain-level content prefix advertisement can be
used to enable efficient interconnection between ASes. Liu et al.
[MLDHT] proposed to address the "suffix-hole" issue found in prefix-
based name aggregation through the use of a combination of Bloom-
filter-based aggregation and multi-level DHT.
Name aggregation has been discussed for a flat naming design, for
example, in [NCOA], in which the authors note that based on
estimations in [DONA] flat naming may not require aggregation. This
is a point that calls for further study. Scenarios evaluating name
aggregation, or lack thereof, should take into account the amount of
state (e.g., size of routing tables) maintained in edge routers as
well as network efficiency (e.g., amount of traffic generated).
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+---------------+
+---------->| Popular Video |
| +---------------+
| ^ ^
| | |
| +-+-+ $0/MB +-+-+
| | A +-------+ B |
| ++--+ +-+-+
| | ^ ^ |
| $8/MB | | | | $10/MB
| v | | v
+-+-+ $0/MB +--+---------+--+
| D +---------+ C |
+---+ +---------------+
Figure 5. Relationships and Transit Costs between Networks A to D
DiBenedetto et al. [RP-NDN] study policy knobs made available by NDN
to network operators. New policies that are not feasible in the
current Internet are described, including a "cache sharing peers"
policy, where two peers have an incentive to share content cached in,
but not originating from, their respective network. The simple
example used in the investigation considers several networks and
associated transit costs, as shown in Figure 5 (based on Figure 1 of
[RP-NDN]). Agyapong and Sirbu [EconICN] further establish that ICN
approaches should incorporate features that foster (new) business
relationships. For example, publishers should be able to indicate
their willingness to partake in the caching market, proper reporting
should be enabled to avoid fraud, and content should be made
cacheable as much as possible to increase cache hit ratios.
Kutscher et al. [SAIL-B3] enable network interactions in the NetInf
architecture using a name resolution service at domain edge routers
and a BGP-like routing system in the NetInf Default-Free Zone.
Business models and incentives are studied in [SAIL-A7] and
[SAIL-A8], including scenarios where the access network provider (or
a virtual CDN) guarantees QoS to end users using ICN. Figure 6
illustrates a typical scenario topology from this work that involves
an interconnectivity provider.
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+----------+ +-----------------+ +------+
| Content | | Access Network/ | | End |
| Provider +---->| ICN Provider +---->| User |
+----------+ +-+-------------+-+ +------+
| |
| |
v v
+-------------------+ +----------------+ +------+
| Interconnectivity | | Access Network | | End |
| Provider +---->| Provider +------>| User |
+-------------------+ +----------------+ +------+
Figure 6. Setup and Operating Costs of Network Entities
Jokela et al. [LIPSIN] propose a two-layer approach where additional
rendezvous systems and topology formation functions are placed
logically above multiple networks and enable advertising and routing
content between them. Visala et al. [LANES] further describe an ICN
architecture based on similar principles, which, notably, relies on a
hierarchical DHT-based rendezvous interconnect. Rajahalme et al.
[PSIRP1] describe a rendezvous system using both a BGP-like routing
protocol at the edge and a DHT-based overlay at the core. Their
evaluation model is centered around policy-compliant path stretch,
latency introduced by overlay routing, caching efficacy, and load
distribution.
Rajahalme et al. [ICCP] point out that ICN architectural changes may
conflict with the current tier-based peering model. For example,
changes leading to shorter paths between ISPs are likely to meet
resistance from Tier-1 ISPs. Rajahalme [IDMcast] shows how
incentives can help shape the design of specific ICN aspects, and in
[IDArch] he presents a modeling approach to exploit these incentives.
This includes a network model that describes the relationship between
Autonomous Systems based on data inferred from the current Internet,
a traffic model taking into account business factors for each AS, and
a routing model integrating the valley-free model and policy
compliance. A typical scenario topology is illustrated in Figure 7,
which is redrawn here based on Figure 1 of [ICCP]. Note that it
relates well with the topology illustrated in Figure 1 of this
document.
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o-----o
+-----+ J +-----+
| o--*--o |
| * |
o--+--o * o--+--o
| H +-----------+ I |
o-*-*-o * o-*-*-o
* * * * *
****** ******* * ******* *******
* * * * *
o--*--o o*-*-*o o--*--o
| E +--------+ F +---------+ G +
o-*-*-o o-----o o-*-*-o
* * * *
****** ******* ****** ******
* * * *
o--*--o o--*--o o--*--o o--*--o
| A | | B +-----------+ C | | D |
o-----o o--+--o o--+--o o----+o
| | ^^ | route
data | data | data || | to
| | || | data
o---v--o o---v--o o++--v-o
| User | | User | | Data |
o------o o------o o------o
Legend:
***** Transit link
+---+ Peering link
+---> Data delivery or route to data
Figure 7. Tier-Based Set of Interconnections between AS A to J
To sum up, the evaluation of ICN architectures across multiple
network types should include a combination of technical and economic
aspects, capturing their various interactions. These scenarios aim
to illustrate scalability, efficiency, and manageability, as well as
traditional and novel network policies. Moreover, scenarios in this
category should specifically address how different actors have proper
incentives, not only in a pure ICN realm, but also during the
migration phase towards this final state.
3.2. Energy Efficiency
ICN has prominent features that can be taken advantage of in order to
significantly reduce the energy footprint of future communication
networks. Of course, one can argue that specific ICN network
elements may consume more energy than today's conventional network
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equipment due to the potentially higher energy demands for named-data
processing en route. On balance, however, ICN introduces an
architectural approach that may compensate on the whole and can even
achieve higher energy efficiency rates when compared to the host-
centric paradigm.
We elaborate on the energy efficiency potential of ICN based on three
categories of ICN characteristics. Namely, we point out that a) ICN
does not rely solely on end-to-end communication, b) ICN enables
ubiquitous caching, and c) ICN brings awareness of user requests (as
well as their corresponding responses) at the network layer thus
permitting network elements to better schedule their transmission
patterns.
First, ICN does not mandate perpetual end-to-end communication, which
introduces a whole range of energy consumption inefficiencies due to
the extensive signaling, especially in the case of mobile and
wirelessly connected devices. This opens up new opportunities for
accommodating sporadically connected nodes and could be one of the
keys to an order-of-magnitude decrease in energy consumption compared
to the potential contributions of other technological advances. For
example, web applications often need to maintain state at both ends
of a connection in order to verify that the authenticated peer is up
and running. This introduces keep-alive timers and polling behavior
with a high toll on energy consumption. Pentikousis [EEMN] discusses
several related scenarios and explains why the current host-centric
paradigm, which employs perpetual end-to-end connections, introduces
built-in energy inefficiencies, and argues that patches to make
currently deployed protocols energy-aware cannot provide for an
order-of-magnitude increase in energy efficiency.
Second, ICN network elements come with built-in caching capabilities,
which is often referred to as "ubiquitous caching". Pushing data
objects to caches closer to end-user devices, for example, could
significantly reduce the amount of transit traffic in the core
network, thereby reducing the energy used for data transport. Guan
et al. [EECCN] study the energy efficiency of a CCNx architecture
(based on their proposed energy model) and compare it with
conventional content dissemination systems such as CDNs and P2P.
Their model is based on the analysis of the topological structure and
the average hop length from all consumers to the nearest cache
location. Their results show that an information-centric approach
can be more energy efficient in delivering popular and small-size
content. In particular, they also note that different network-
element design choices (e.g., the optical bypass approach) can be
more energy efficient in delivering infrequently accessed content.
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Lee et al. [EECD] investigate the energy efficiency of various
network devices deployed in access, metro, and core networks for both
CDNs and ICN. They use trace-based simulations to show that an ICN
approach can substantially improve the network energy efficiency for
content dissemination mainly due to the reduction in the number of
hops required to obtain a data object, which can be served by
intermediate nodes in ICN. They also emphasize that the impact of
cache placement (in incremental deployment scenarios) and
local/cooperative content replacement strategies needs to be
carefully investigated in order to better quantify the energy
efficiencies arising from adopting an ICN paradigm.
Third, ICN elements are aware of the user request and its
corresponding data response; due to the nature of name-based routing,
they can employ power consumption optimization processes for
determining their transmission schedule or powering down inactive
network interfaces. For example, network coding [NCICN] or adaptive
video streaming [COAST] can be used in individual ICN elements so
that redundant transmissions, possibly passing through intermediary
networks, could be significantly reduced, thereby saving energy by
avoiding carrying redundant traffic.
Alternatively, approaches that aim to simplify routers, such as
[PURSUIT], could also reduce energy consumption by pushing routing
decisions to a more energy-efficient entity. Along these lines, Ko
et al. [ICNDC] design a data center network architecture based on ICN
principles and decouple the router control-plane and data-plane
functionalities. Thus, data forwarding is performed by simplified
network entities, while the complicated routing computation is
carried out in more energy-efficient data centers.
To summarize, energy efficiency has been discussed in ICN evaluation
studies, but most published work is preliminary in nature. Thus, we
suggest that more work is needed in this front. Evaluating energy
efficiency does not require the definition of new scenarios or
baseline topologies, but does require the establishment of clear
guidelines so that different ICN approaches can be compared not only
in terms of scalability, for example, but also in terms of power
consumption.
3.3. Operation across Multiple Network Paradigms
Today the overwhelming majority of networks are integrated with the
well-connected Internet with IP at the "waist" of the technology
hourglass. However, there is a large amount of ongoing research into
alternative paradigms that can cope with conditions other than the
standard set assumed by the Internet. Perhaps the most advanced of
these is Delay- and Disruption-Tolerant Networking (DTN). DTN is
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considered as one of the scenarios for the deployment in Section 2.7,
but here we consider how ICN can operate in an integrated network
that has essentially disjoint "domains" (a highly overloaded term!)
or regions that use different network paradigms and technologies, but
with gateways that allow interoperation.
ICN operates in terms of named data objects so that requests and
deliveries of information objects can be independent of the
networking paradigm. Some researchers have contemplated some form of
ICN becoming the new waist of the hourglass as the basis of a future
reincarnation of the Internet, e.g., [ArgICN], but there are a large
number of problems to resolve, including authorization, access
control, and transactional operation for applications such as
banking, before some form of ICN can be considered as ready to take
over from IP as the dominant networking technology. In the meantime,
ICN architectures will operate in conjunction with existing network
technologies as an overlay or in cooperation with the lower layers of
the "native" technology.
It seems likely that as the reach of the "Internet" is extended,
other technologies such as DTN will be needed to handle scenarios
such as space communications where inherent delays are too large for
TCP/IP to cope with effectively. Thus, demonstrating that ICN
architectures can work effectively in and across the boundaries of
different networking technologies will be important.
The NetInf architecture, in particular, targets the inter-domain
scenario by the use of a convergence-layer architecture [SAIL-B3],
and Publish-Subscribe Internet Routing Paradigm (PSIRP) and/or
Publish-Subscribe Internet Technology (PURSUIT) is envisaged as a
candidate for an IP replacement.
The key items for evaluation over and above the satisfactory
operation of the architecture in each constituent domain will be to
ensure that requests and responses can be carried across the network
boundaries with adequate performance and do not cause malfunctions in
applications or infrastructure because of the differing
characteristics of the gatewayed domains.
4. Summary
This document presents a wide range of different application areas in
which the use of information-centric network designs have been
evaluated in the peer-reviewed literature. Evidently, this broad
range of scenarios illustrates the capability of ICN to potentially
address today's problems in an alternative and better way than host-
centric approaches as well as to point to future scenarios where ICN
may be applicable. We believe that by putting different ICN systems
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to the test in diverse application areas, the community will be
better equipped to judge the potential of a given ICN proposal and
therefore subsequently invest more effort in developing it further.
It is worth noting that this document collected different kinds of
considerations, as a result of our ongoing survey of the literature
and the discussion within ICNRG, which we believe would have
otherwise remained unnoticed in the wider community. As a result, we
expect that this document can assist in fostering the applicability
and future deployment of ICN over a broader set of operations, as
well as possibly influencing and enhancing the base ICN proposals
that are currently available and possibly assist in defining new
scenarios where ICN would be applicable.
We conclude this document with a brief summary of the evaluation
aspects we have seen across a range of scenarios.
The scalability of different mechanisms in an ICN architecture stands
out as an important concern (cf. Sections 2.1, 2.2, 2.5, 2.6, 2.8,
2.9, and 3.1) as does network, resource, and energy efficiency (cf.
Sections 2.1, 2.3, 2.4, 3.1, and 3.2). Operational aspects such as
network planing, manageability, reduced complexity and overhead (cf.
Sections 2.2, 2.3, 2.4, 2.8, and 3.1) should not be neglected
especially as ICN architectures are evaluated with respect to their
potential for deployment in the real world. Accordingly, further
research in economic aspects as well as in the communication,
computation, and storage tradeoffs entailed in each ICN architecture
is needed.
With respect to purely technical requirements, support for multicast,
mobility, and caching lie at the core of many scenarios (cf. Sections
2.1, 2.3, 2.5, and 2.6). ICN must also be able to cope when the
Internet expands to incorporate additional network paradigms (cf.
Section 3.3). We have also seen that being able to address stringent
QoS requirements and increase reliability and resilience should also
be evaluated following well-established methods (cf. Sections 2.2,
2.8, and 2.9).
Finally, we note that new applications that significantly improve the
end-user experience and forge a migration path from today's host-
centric paradigm could be the key to a sustained and increasing
deployment of the ICN paradigm in the real world (cf. Sections 2.2,
2.3, 2.6, 2.8, and 2.9).
5. Security Considerations
This document does not impact the security of the Internet.
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6. Informative References
[RFC5743] Falk, A., "Definition of an Internet Research Task Force
(IRTF) Document Stream", RFC 5743, December 2009,
<http://www.rfc-editor.org/info/rfc5743>.
[RFC5050] Scott, K. and S. Burleigh, "Bundle Protocol
Specification", RFC 5050, November 2007,
<http://www.rfc-editor.org/info/rfc5050>.
[RFC4838] Cerf, V., Burleigh, S., Hooke, A., Torgerson, L., Durst,
R., Scott, K., Fall, K., and H. Weiss, "Delay-Tolerant
Networking Architecture", RFC 4838, April 2007,
<http://www.rfc-editor.org/info/rfc4838>.
[RFC5568] Koodli, R., Ed., "Mobile IPv6 Fast Handovers", RFC 5568,
July 2009, <http://www.rfc-editor.org/info/rfc5568>.
[RFC6920] Farrell, S., Kutscher, D., Dannewitz, C., Ohlman, B.,
Keranen, A., and P. Hallam-Baker, "Naming Things with
Hashes", RFC 6920, April 2013,
<http://www.rfc-editor.org/info/rfc6920>.
[NetInf] Ahlgren, B. et al., "Design considerations for a network
of information", Proc. CoNEXT Re-Arch Workshop, ACM, 2008.
[CCN] Jacobson, V., et al., "Networking Named Content", Proc.
CoNEXT, ACM, 2009.
[CCNx] Mosko, M., Solis, I., and E. Uzun, "CCN 1.0 Protocol
Architecture", Project CCNx documentation, Xerox Palo Alto
Research Center, 2013,
<http://ccnx.org/pubs/ICN_CCN_Protocols.pdf>.
[NDNP] Zhang, L., et al., "Named Data Networking (NDN) Project",
NDN Technical Report NDN-0001, Oct. 2010,
<http://named-data.net/publications/techreports/>.
[PSI] Trossen, D. and G. Parisis, "Designing and realizing an
information-centric internet", IEEE Commun. Mag., vol. 50,
no. 7, July 2012.
[DONA] Koponen, T., et al., "A Data-Oriented (and Beyond) Network
Architecture", Proc. SIGCOMM, ACM, 2007.
[SoA1] Ahlgren, B., et al., "A survey of information-centric
networking", IEEE Commun. Mag., vol. 50, no. 7, July 2012.
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[SoA2] Xylomenos, G., et al. "A survey of information-centric
networking research", IEEE Communications Surveys and
Tutorials (2013): 1-26.
[ICN-SN] Mathieu, B., et al., "Information-centric networking: a
natural design for social network applications", IEEE
Commun. Mag., vol. 50, no. 7, July 2012.
[VPC] Kim, J., et al., "Content Centric Network-based Virtual
Private Community", Proc. ICCE, IEEE, 2011.
[CBIS] Jacobson, V., et al., "Custodian-Based Information
Sharing", IEEE Commun. Mag., vol. 50, no. 7, July 2012.
[VPC2] Kim, D. and J. Lee, "CCN-based virtual private community
for extended home media service", IEEE Trans. Consumer
Electronics, vol. 57, no. 2, May 2011.
[CCR] Arianfar, S., et al., "On content-centric router design
and implications", Proc. CoNEXT Re-Arch Workshop, ACM,
2010.
[VoCCN] Jacobson, V., et al., "VoCCN: Voice-over Content-Centric
Networks", Proc. CoNEXT Re-Arch Workshop, ACM, 2009.
[NDNpb] Xuan, Y. and Z. Yan, "Enhancing Routing Efficiency in
Named Data Network with Piggybacked Interest", Proc. CFI,
ACM, 2013.
[ACT] Zhu, Z., et al., "ACT: Audio Conference Tool Over Named
Data Networking", Proc. SIGCOMM ICN Workshop, ACM, 2011.
[G-COPSS] Chen, J., et al., "G-COPSS: A Content Centric
Communication Infrastructure for Gaming Applications",
Proc. ICDCS, IEEE, 2012.
[MMIN] Pentikousis, K., and P. Bertin., "Mobility Management in
Infrastructure Networks", IEEE Internet Computing 17, no.
5 (2013): 74-79.
[SCES] Allman, M., et al., "Enabling an Energy-Efficient Future
Internet through Selectively Connected End Systems", Proc.
HotNets-VI, ACM, 2007.
[EEMN] Pentikousis, K., "In Search of Energy-Efficient Mobile
Networking", IEEE Commun. Mag., vol. 48, no. 1, Jan. 2010.
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[MOBSURV] Tyson, G., et al., "A Survey of Mobility in Information-
Centric Networks: Challenges and Research Directions",
Proc. MobiHoc Workshop on Emerging Name-Oriented Mobile
Networking Design, ACM, 2012.
[N-Scen] Dannewitz, C., et al., "Scenarios and research issues for
a Network of Information", Proc. MobiMedia, ICST, 2012.
[DTI] Ott, J. and D. Kutscher, "Drive-thru Internet: IEEE
802.11b for 'automobile' users", Proc. INFOCOM, IEEE,
2004.
[PSIMob] Xylomenos, G., et al., "Caching and Mobility Support in a
Publish-Subscribe Internet Architecture", IEEE Commun.
Mag., vol. 50, no. 7, July 2012.
[mNetInf] Pentikousis, K. and T. Rautio, "A Multiaccess Network of
Information", Proc. WoWMoM, IEEE, 2010.
[HybICN] Lindgren, A., "Efficient content distribution in an
information-centric hybrid mobile networks", Proc. CCNC,
IEEE, 2011.
[E-CHANET] M. Amadeo, et al., "E-CHANET: Routing, Forwarding and
Transport in Information-Centric Multihop Wireless
Networks", Computer Communications, Elsevier, Jan. 2013
online.
[MobiA] Meisel, M., et al., "Ad Hoc Networking via Named Data",
Proc. MobiArch, ACM 2010.
[CCNMANET] Oh, S. Y., et al., "Content Centric Networking in Tactical
and Emergency MANETs", Proc. Wireless Days, IFIP, 2010.
[RTIND] Wang, L., et al., "Rapid Traffic Information Dissemination
Using Named Data", Proc. MobiHoc NoM workshop, ACM, 2012.
[CCNVANET] Amadeo, M., et al., "Content-Centric Networking: is that a
Solution for Upcoming Vehicular Networks?", Proc. VANET,
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[ABC] Gustafsson, E., and A. Jonsson. "Always best connected",
Wireless Communications, IEEE 10.1 (2003): 49-55.
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performance in information centric networking", Proc.
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Pentikousis, et al. Informational [Page 38]
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[CL4M] Chai, W. K., et al., "Cache 'Less for More' in
Information-centric Networks", Proc. Networking, IFIP,
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[CCNCT] Psaras, I., et al., "Modelling and Evaluation of CCN-
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Content-Centric Networks", Proc. ICCCN, IEEE, 2012.
[CURLING] Chai, W. K., et al., "CURLING: Content-Ubiquitous
Resolution and Delivery Infrastructure for Next-Generation
Services", IEEE Commun. Mag., vol. 49, no. 3, Mar. 2011.
[ACDICN] Fotiou, N., et al., "Access control enforcement delegation
for information-centric networking architectures", Proc.
SIGCOMM ICN Workshop, ACM, 2012.
[EWC] Bai, F. and B. Krishnamachari, "Exploiting the wisdom of
the crowd: localized, distributed information-centric
VANETs", IEEE Commun. Mag., vol. 48, no. 5, May 2010.
[DMND] Wang, J., R. Wakikawa, and L. Zhang, "DMND: Collecting
data from mobiles using Named Data", Proc. Vehicular
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Communications", Proc. INFOCOM NOMEN workshop, IEEE, 2012.
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Network Model for Hybrid Vehicular Ad-Hoc Networks". Proc.
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[CCDIVN] TalebiFard, P. and V.C.M. Leung, "A Content Centric
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Vehicular Ad Hoc Networks", IEEE Communications Letters,
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[SCN] Hoydis, J., et al., "Green small-cell networks", IEEE
Vehicular Technology Magazine, vol. 6, no.1, pp. 37-43,
March 2011.
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[HetNet] Li, H., et al. "Efficient HetNet implementation using
broadband wireless access with fiber-connected massively
distributed antennas architecture", IEEE Wireless
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Architectures", Proc. SIGCOMM ICN Workshop, ACM, 2011.
[RP-NDN] DiBenedetto, S., et al., "Routing policies in named data
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D-A.7, Aug. 2011,
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[SAIL-A8] Zhang, N., Ed., et al., "Evaluation of business models",
SAIL Project Deliverable D-A.8, Jan. 2013,
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[LIPSIN] Jokela, P., et al., "LIPSIN: line speed publish/subscribe
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Architecture", PSIRP Technical Report TR09-003, Dec. 2009.
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[ICCP] Rajahalme J., et al., "Incentive-Compatible Caching and
Peering in Data-Oriented Networks", Proc. CoNEXT Re-Arch
Workshop, ACM, 2008.
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[PURSUIT] Fotiou, N., et al., "Developing Information Networking
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[EECCN] Guan, K., et al., "On the Energy Efficiency of Content
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[EECD] Lee, U., Rimac, I., Kilper, D., and V. Hilt, "Toward
energy-efficient content dissemination", IEEE Network,
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[NCICN] Montpetit, M. J., Westphal, C., and D. Trossen, "Network
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[COAST] Gruneberg, K., et al., "File format specification and 3D
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[ICNDC] Ko, B. J., Pappas, V., Raghavendra, R., Song, Y.,
Dilmaghani, R. B., Lee, K.-w., and D. Verma, "An
information-centric architecture for data center
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challenged internets", Proc. SIGCOMM, ACM, 2003.
[DTNICN] Tyson, G., Bigham, J., and E. Bodanese, "Towards an
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"Bundle Protocol Query Extension Block", Work in Progress,
draft-irtf-dtnrg-bpq-00, May 2012.
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[SLINKY] Kawadia, V., Riga, N., Opper, J., and D. Sampath, "Slinky:
An adaptive protocol for content access in disruption-
tolerant ad hoc networks", in Proc. MobiHoc Workshop on
Tactical Mobile Ad Hoc Networking, 2011.
[ONE] "The Opportunistic Network Environment simulator",
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[TWIMIGHT] Hossmann, T., et al. "Twitter in disaster mode: smart
probing for opportunistic peers", Proc. 3rd ACM
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[MODEL1] Uddin, M.Y.S., Nicol, D.M., Abdelzaher, T.F., and R.H.
Kravets, "A post-disaster mobility model for Delay
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[MODEL2] Aschenbruck, N., Gerhards-Padilla, E., and P. Martini,
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[CIBUS] Biswas, T., et al., "Contextualized Information-Centric
Home Network", Proc. ACM SIGCOMM, ACM, 2013.
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[Homenet] Ravindran, R., et al., "Information-centric Networking
based Homenet", Proc. International Workshop on Management
of the Future Internet (ManFI), IFIP/IEEE, 2013.
[IoTScope] Marias, G.F., et al., "Efficient information lookup for
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[iHEMS] Zhang, J., et al., "iHEMS: An Information-Centric Approach
to Secure Home Energy Management", Proc. SmartGridComm,
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[ACC] Andreini, F., et al., "A scalable architecture for geo-
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[EVAL-METHOD]
Pentikousis, K., Ed., Ohlman, B., Davies, E., Spirou, S.,
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Networking: Evaluation Methodology", Work in Progress,
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[CHALLENGES]
Kutscher, D., Ed., Eum, S., Pentikousis, K., Psaras, I.,
Corujo, D., Saucez, D., Schmidt, T., and M. Waehlisch,
"ICN Research Challenges", Work in Progress, draft-irtf-
icnrg-challenges-01, February 2015.
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Acknowledgments
Dorothy Gellert contributed to an earlier draft version of this
document.
This document has benefited from reviews, pointers to the growing ICN
literature, suggestions, comments, and proposed text provided by the
following members of the IRTF Information-Centric Networking Research
Group (ICNRG), listed in alphabetical order: Marica Amadeo, Hitoshi
Asaeda, Claudia Campolo, Luigi Alfredo Grieco, Myeong-Wuk Jang, Ren
Jing, Will Liu, Hongbin Luo, Priya Mahadevan, Ioannis Psaras, Spiros
Spirou, Dirk Trossen, Jianping Wang, Yuanzhe Xuan, and Xinwen Zhang.
The authors would like to thank Mark Stapp, Juan Carlos Zuniga, and
G.Q. Wang for their comments and suggestions as part of their open
and independent review of this document within ICNRG.
Authors' Addresses
Kostas Pentikousis (editor)
EICT GmbH
Torgauer Strasse 12-15
10829 Berlin
Germany
EMail: k.pentikousis@eict.de
Borje Ohlman
Ericsson Research
S-16480 Stockholm
Sweden
EMail: Borje.Ohlman@ericsson.com
Daniel Corujo
Instituto de Telecomunicacoes
Campus Universitario de Santiago
P-3810-193 Aveiro
Portugal
EMail: dcorujo@av.it.pt
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Gennaro Boggia
Dep. of Electrical and Information Engineering
Politecnico di Bari
Via Orabona 4
70125 Bari
Italy
EMail: g.boggia@poliba.it
Gareth Tyson
School and Electronic Engineering and Computer Science
Queen Mary, University of London
United Kingdom
EMail: gareth.tyson@eecs.qmul.ac.uk
Elwyn Davies
Trinity College Dublin/Folly Consulting Ltd
Dublin, 2
Ireland
EMail: davieseb@scss.tcd.ie
Antonella Molinaro
Dep. of Information, Infrastructures, and Sustainable
Energy Engineering
Universita' Mediterranea di Reggio Calabria
Via Graziella 1
89100 Reggio Calabria
Italy
EMail: antonella.molinaro@unirc.it
Suyong Eum
National Institute of Information and Communications Technology
4-2-1, Nukui Kitamachi, Koganei
Tokyo 184-8795
Japan
Phone: +81-42-327-6582
EMail: suyong@nict.go.jp
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