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| author | Thomas Voss <mail@thomasvoss.com> | 2024-11-27 20:54:24 +0100 |
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| committer | Thomas Voss <mail@thomasvoss.com> | 2024-11-27 20:54:24 +0100 |
| commit | 4bfd864f10b68b71482b35c818559068ef8d5797 (patch) | |
| tree | e3989f47a7994642eb325063d46e8f08ffa681dc /doc/rfc/rfc2123.txt | |
| parent | ea76e11061bda059ae9f9ad130a9895cc85607db (diff) | |
doc: Add RFC documents
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diff --git a/doc/rfc/rfc2123.txt b/doc/rfc/rfc2123.txt new file mode 100644 index 0000000..5020544 --- /dev/null +++ b/doc/rfc/rfc2123.txt @@ -0,0 +1,1907 @@ + + + + + + +Network Working Group N. Brownlee +Request for Comments: 2123 The University of Auckland +Category: Informational March 1997 + + + Traffic Flow Measurement: Experiences with NeTraMet + +Status of this Memo + + This memo provides information for the Internet community. This memo + does not specify an Internet standard of any kind. Distribution of + this memo is unlimited. + +Abstract + + This memo records experiences in implementing and using the Traffic + Flow Measurement Architecture and Meter MIB. It discusses the + implementation of NeTraMet (a traffic meter) and NeMaC (a combined + manager and meter reader), considers the writing of meter rule sets + and gives some guidance on setting up a traffic flow measurement + system using NeTraMet. + +Table of Contents + + 1 Introduction 2 + 1.1 NeTraMet structure and development . . . . . . . . . . . . . . 3 + 1.2 Scope of this document . . . . . . . . . . . . . . . . . . . . 4 + 2 Implementation 4 + 2.1 Choice of meter platform . . . . . . . . . . . . . . . . . . . 4 + 2.2 Programming support requirements . . . . . . . . . . . . . . . 5 + 2.2.1 DOS environment . . . . . . . . . . . . . . . . . . . . . 6 + 2.2.2 Unix environment . . . . . . . . . . . . . . . . . . . . . 7 + 2.3 Implementing the meter . . . . . . . . . . . . . . . . . . . . 7 + 2.3.1 Data structures . . . . . . . . . . . . . . . . . . . . . 7 + 2.3.2 Packet matching . . . . . . . . . . . . . . . . . . . . . 8 + 2.3.3 Testing groups of rule addresses . . . . . . . . . . . . . 8 + 2.3.4 Compression of address masks . . . . . . . . . . . . . . . 9 + 2.3.5 Ignoring unwanted flow data . . . . . . . . . . . . . . . 10 + 2.3.6 Observing meter reader activity . . . . . . . . . . . . . 11 + 2.3.7 Meter memory management . . . . . . . . . . . . . . . . . 12 + 2.4 Data collection . . . . . . . . . . . . . . . . . . . . . . . 14 + 2.5 Restarting a meter . . . . . . . . . . . . . . . . . . . . . . 15 + 2.6 Performance . . . . . . . . . . . . . . . . . . . . . . . . . 16 + 3 Writing rule sets 16 + 3.1 Rule set to observe all flows . . . . . . . . . . . . . . . . 17 + 3.2 Specifying flow direction, using computed attributes . . . . . 18 + 3.3 Subroutines . . . . . . . . . . . . . . . . . . . . . . . . . 21 + 3.4 More complicated rule sets . . . . . . . . . . . . . . . . . . 23 + + + +Brownlee Informational [Page 1] + +RFC 2123 Traffic Flow Measurement March 1997 + + + 4 Flow data files 26 + 4.1 Sample flow data file . . . . . . . . . . . . . . . . . . . . 27 + 4.2 Flow data file features . . . . . . . . . . . . . . . . . . . 28 + 4.3 Terminating and restarting meter reading . . . . . . . . . . . 29 + 5 Analysis applications 30 + 6 Using NeTraMet in a measurement system 31 + 6.1 Examples of NeTraMet in production use . . . . . . . . . . . . 31 + 7 Acknowledgments 33 + 8 References 33 + 9 Security Considerations 34 +10 Author's Address 34 + +1 Introduction + + Early in 1992 my University needed to develop a system for recovering + the costs of its Internet traffic. In March of that year I attended + the Internet Accounting Working Group's session at the San Diego + IETF, where I was delighted to find that the Group had produced a + detailed architecture for measuring network traffic and were waiting + for someone to try implementing it. + + During 1992 I produced a prototype measurement system, using balanced + binary trees to store information about traffic flows. This work was + reported at the Washington IETF in November 1992. The prototype + performed well, but it made no attempt to recover memory from old + flows, and the overheads in managing the balanced trees proved to be + unacceptably high. I moved on to develop a production-quality + system, this time using hash tables to index the flow information. + + This version was called NeTraMet (the Network Traffic Meter), and was + released as free software in October 1993. Since then I have + continued working on NeTraMet, producing new releases two or three + times each year. NeTraMet is now in production use at many sites + around the world. It is difficult to estimate the number of sites, + but there is an active NeTraMet mailing list, which had about 130 + subscribers in March 1996. + + Early in 1996 the Realtime Traffic Flow Measurement Working Group + (RTFM) was chartered to move the Traffic Flow Measurement + Architecture on to the IETF standards track. This document records + traffic flow measurement experience gained through three years + experience with NeTraMet. + + + + + + + + + +Brownlee Informational [Page 2] + +RFC 2123 Traffic Flow Measurement March 1997 + + +1.1 NeTraMet structure and development + + The Traffic Flow Architecture document [1] describes four components: + + - METERS, which are attached to the network at the points where + it is desired to measure the traffic, + + - METER READERS, which read data from meters and store it for later + use, + + - MANAGERS, which configure meters and control meter readers, and + + - ANALYSIS APPLICATIONS, which process the data from meter readers + so as to produce whatever reports are required. + + NeTraMet is a computer program which implements the Traffic Meter, + stores the measured flow data in memory, and provides an SNMP agent + so as to make it available to Meter Readers. The NeTraMet + distribution files include NeMaC, which is a combined Manager and + Meter Reader capable of managing an arbitrary number of meters, each + of which may be using its own rule set, and having its flow data + collected at its own specified intervals. The NeTraMet distribution + also includes several rudimentary Analysis Applications, allowing + users to produce simple plots from NeMaC's flow data files (fd_filter + and fd_extract) and to monitor - in real time - the flows at a remote + meter (nm_rc and nifty). + + Since the first release the Traffic Meter MIB [2] has been both + improved and simplified. Significant changes have included better + ways to specify traffic flows (i.e. more actions and better control + structures for the Packet Matching Engine), and computed attributes + (class and kind). These changes have been prompted by operational + requirements at sites using NeTraMet, and have been tested + extensively in successive versions of NeTraMet. + + NeTraMet is widely used to collect usage data for Internet Service + Providers. This is especially so in Australia and New Zealand, but + there are also active users at sites around the world, for example in + Canada, France, Germany and Poland. + + NeTraMet is very useful as a tool for understanding exactly where + traffic is flowing in large networks. Since the Traffic Meters + perform considerable data reduction (as specified by their rule sets) + they significantly reduce the volume of data to be read by Meter + Readers. This characteristic makes NeTraMet particularly effective + for networks with many remote sites. An example of this (the + Kawaihiko network) is briefly described below. + + + + +Brownlee Informational [Page 3] + +RFC 2123 Traffic Flow Measurement March 1997 + + + As well as providing data for post-observation analysis, NeTraMet can + be used for real-time network monitoring and trouble-shooting. The + NeTraMet distribution includes 'nifty,' an X/Motif application which + monitors traffic flows and attempts to highlight those which are + 'interesting.' + +1.2 Scope of this document + + This document presents the experience gained from three years work + with the Traffic Flow Measurement Architecture. Its contents are + grouped as follows + + - Implementation issues for NeTraMet and NeMaC, + + - How rule files work, and how to write them for particular + purposes, and + + - How to use NeTraMet and NeMaC for short-term and long-term flow + measurement. + +2 Implementation + +2.1 Choice of meter platform + + As pointed out in the Architecture document [1], the goal of the + Realtime Traffic Flow Measurement Working Group is to develop a + standard for the Traffic Meter, with the goal of seeing it + implemented in network devices such as hubs, switches and routers. + Until the Architecture is well enough developed to allow this, it has + sufficed to implement the meter as a program running on a general- + purpose computer system. + + The choice of computer system for NeTraMet was driven by the need to + choose one which would be widely available within the Internet + community. One strong possibility was a Unix system, since these are + commonly used for a variety of network support and management tasks. + For the initial implementation, however, Unix would have had some + disadvantages: + + - The wide variety of different Unix systems can increase the + difficulties of software support. + + - The cost of a Unix system as a meter is too high to allow users + to run meters simultaneously at many points within their + networks. + + + + + + +Brownlee Informational [Page 4] + +RFC 2123 Traffic Flow Measurement March 1997 + + + Another factor in choosing the platform was system performance. When + I first started implementing NeTraMet it was impossible to predict + how much processing workload was needed for a viable meter. + Similarly, I had no idea how much memory would be required for code + or data. I therefore chose to implement NeTraMet on a DOS PC. This + was because: + + - It is a minimum system in all respects. If the meter works + well on such a system, it can be implemented on almost any + hardware (including routers, switches, etc.) + + - It is an inexpensive system. Sites can easily afford to have + many meters around their networks. + + - It is a simple system, and one which I had complete control over. + This allowed me to implement effective instrumentation to monitor + the meter's performance, and to include a wide variety of + performance optimisations in the code. + + Once the meter was running I needed a manager to download rule files + to it. Since a single manager and meter reader can effectively + support a large number of meters, a Unix environment for NeMaC was a + natural choice. There are fewer software support problems for NeMaC + than for NeTraMet since NeMaC has minimal support needs - it only + needs to open a UDP socket to the SNMP port on each controlled meter. + + Early NeTraMet distributions contained only the PC meter and Unix + manager. In later releases I ported NeTraMet (the meter) to Unix, + and extended the control features of NeMaC (the combined manager and + meter reader). I have also experimented with porting NeMaC to the + DOS system. This is not difficult, but doesn't seem to be worth + pursuing. + + The current version of NeTraMet is a production-quality traffic + measurement system which has been in continuous use at the University + of Auckland for nearly two years. + +2.2 Programming support requirements + + To implement the Traffic Flow Meter I needed a programming + environment providing good support for the following: + + - observation of packet headers on the network; + + - system timer with better than 10 ms resolution; + + - IP (Internet Protocol), for communications with manager and meter + reader; + + + +Brownlee Informational [Page 5] + +RFC 2123 Traffic Flow Measurement March 1997 + + + - SNMP, for the agent implementing the Meter MIB. + +2.2.1 DOS environment + + For the PC I chose to use Ethernet as the physical network medium. + This is simply an initial choice, being the medium used within the + University of Auckland's data network. Interfaces for other media + could easily be added as they are needed. + + In the PC environment a variety of 'generalised' network interfaces + are available. I considered those available from companies such as + Novell, DEC and Microsoft and decided against them, partly because + they are proprietary, and partly because they did not appear to be + particularly easy to use. Instead I chose the CRYNWR Packet Drivers + [3] . These are available for a wide variety of interface cards and + are simple and clearly documented. They support Ethernet's + promiscuous mode, allowing one to observe headers for every passing + packet in a straightforward manner. One disadvantage of the Packet + Drivers is that it is harder to use them with newer user shells (such + as Microsoft Windows), but this was irrelevant since I intended to + run the meter as the only program on a dedicated machine. + + Timing on the PC presented a challenge since the BIOS timer routines + only provide a clock tick about 18 times each second, which limits + the available time resolution. Initially I made do with a timing + resolution of one second for packets, since I believed that most + flows existed for many seconds. In recent years it has become + apparent that many flows have lifetimes well under a second. To + measure them properly with the Traffic Flow Meter one needs times + resolved to 10 millisecond intervals, this being the size of + TimeTicks, the most common time unit within SNMP [4]. Since all the + details of the original PC are readily available [5], it was not + difficult to understand the underlying hardware. I have written PC + timer routines for NeTraMet which read the hardware timer with 256 + times the resolution of the DOS clock ticks, i.e. about 5 ticks per + millisecond. + + There are many TCP/IP implementations available for DOS, but most of + them are commercial software. Instead I chose Waterloo TCP [6], + since this was available (including full source code) as public + domain software. This was necessary since I needed to modify it to + allow me to save incoming packet headers at the same time as + forwarding packets destined for the meter to the IP handler routines. + For SNMP I chose CMU SNMP [7], since again this was available (with + full source code) as public domain software. This made it fairly + simple to port it from Unix to the PC. + + + + + +Brownlee Informational [Page 6] + +RFC 2123 Traffic Flow Measurement March 1997 + + + Finally, for the NeTraMet development I used Borland's Turbo C and + Turbo Assembler. Although many newer C programming environments are + now available, I have been perfectly happy with Turbo C version 2 for + the NeTraMet project! + +2.2.2 Unix environment + + In implementing the Unix meter, the one obvious problem was 'how do I + get access to packet headers?' Early versions of the Unix meter were + implemented using various system-specific interfaces on a SunOS 4.2 + system. Later versions use libpcap [8], which provides a portable + method of obtaining access to packet headers on a wide range of Unix + systems. I have verified that this works very well for ethernet + interfaces on Solaris, SunOS, Irix, DEC Unix and Linux, and for FDDI + interfaces on Solaris. libpcap provides timestamps for each packet + header with resolution determined by the system clock, which is + certainly better than 10 ms! + + All Unix systems provide TCP/IP capabilities, so that was not an + issue. For SNMP I used CMU SNMP, exactly as on the PC. + +2.3 Implementing the meter + + This section briefly discusses the data structures used by the meter, + and the packet matching process. One very strong concern during the + evolution of NeTraMet has been the need for the highest possible + level of meter performance. A variety of interesting optimisations + have been developed to achieve this; as discussed below. Another + particular concern was the need for efficient and effective memory + managent; this is discussed in detail below. + +2.3.1 Data structures + + All the programs in NeTraMet, NeMaC and their supporting utility + programs are written in C, partly because C and its run-time + libraries provides good access to the underlying hardware, and partly + because I have found it to be a highly portable language. + + + + + + + + + + + + + + +Brownlee Informational [Page 7] + +RFC 2123 Traffic Flow Measurement March 1997 + + + The data for each flow is stored in a C structure. The structure + includes all the flow's attribute values (including packet and byte + counts), together with a link field which can be used to link flows + into lists. NeTraMet assumes that Adjacent addresses are 802 MAC + Addresses, which are all six bytes long. Similarly, Transport + addresses are assumes to be two bytes long, which is the case for + port numbers in IP. Peer addresses are normally four bytes or less + in length. They may, however, be as long as 20 bytes (for CLNS). I + have chosen to use a fixed Peer address size, defined at compile + time, so as to avoid the complexity of having variable-sized flow + structures. + + The flow table itself is an array of pointers to flow data + structures, which allows indexed access to flows via their flow + numbers. There is also a single large hash table, referred to in the + Architecture document [1] as the flow table's 'search index'. Each + hash value in the table points to a circular chain of flows. To find + a flow one computes its hash value then searches that value's flow + chain. + + The meter stores each rule in a C structure. All the rule components + have fixed sizes, but address fields must be wide enough to hold any + type of address - Adjacent, Peer or Transport. The rule address + width is defined at compile time, in the same way as flow Peer + addresses. Each rule set is implemented as an array of pointers to + rule data structures, and the rule table is an array of pointers to + the rule sets. The size of each rule set is specified by NeMaC + (before it begins downloading the rule set), but the maximum number + of rule sets is defined at compile time. + +2.3.2 Packet matching + + Packet matching is carried out in NeTraMet exactly as described in + the Architecture document [1]. Each incoming packet header is + analysed so as to determine its attribute values. These values are + stored in a structure which is passed to the Packet Matching Engine. + To facilitate matching with source and destination reversed this + structure contains two substructures, one containing the source + Adjacent, Peer and Transport address values, the other containing the + destination address values. + +2.3.3 Testing groups of rule addresses + + As described in the Architecture [1] each rule's address will usually + be tested, i.e. ANDed with the rule's mask and compared with the + rule's value. If the comparison fails, the next rule in sequence is + executed. This allows one to write rule sets which use a group of + rules to test an incoming packet to see whether one of its addresses + + + +Brownlee Informational [Page 8] + +RFC 2123 Traffic Flow Measurement March 1997 + + + - e.g. its SourcePeerAddress - is one of a set of specified IP + addresses. Such groups of related rules can grow quite large, + containing hundreds of rules. It was clear that sequential execution + of such groups of rules would be slow, and that something better was + essential. + + The optimisation implemented in NeTraMet is to find groups of rules + which test the same attribute with the same mask, and convert them + into a single hashed search of their values. The overhead of setting + up hash tables (one for each group) is incurred once, just before the + meter starts running a new rule set. When a 'group' test is to be + performed, the meter ANDs the incoming attribute value, computes a + hash value from it, and uses this to search the group's hash table. + Early tests showed that the rule hash chains were usually very short, + usually having only one or two members. The effect is to reduce + large sequences of tests to a hash computation and lookup, with a + very small number of compares; in short this is an essential + optimisation for any traffic meter! + + There is, of course, overhead associated with performing the hashed + compare. NeTraMet handles this by having a minimum group size + defined at compile time. If the group is too small it is not + combined into a hashed group. + + In early versions of NeTraMet I did not allow Gotos into a hashed + group of rules, which proved to be an unnecessarily conservative + position. NeTraMet stores each group's hash table in a separate + memory area, and keeps a pointer to the hash table in the first rule + of the group. (The rules data structure has an extra component to + hold this hash table pointer). Rules within the group don't have + hash table pointers; when they are executed as the target of a Goto + rule they behave as ordinary rules, i.e. their tests are performed + normally. + +2.3.4 Compression of address masks + + When the Packet Matching Engine has decided that an incoming packet + belongs to a flow which is to be measured, it searches the flow table + to determine whether or not the flow is already present. It does + this by computing a hash from the packet and using it for access to + the flow table's search index. + + When designing a hash table, one normally assumes that the objects in + the table have a constant size. For NeTraMet's flow table this would + mean that each flow would contain a value for every attribute. This, + however, is not the case, since only those attribute values 'pushed' + by rules during packet matching are stored for a flow. + + + + +Brownlee Informational [Page 9] + +RFC 2123 Traffic Flow Measurement March 1997 + + + To demonstrate this problem , let us assume that every flow in the + table contains a value for only one attribute, SourcePeerAddress, and + that the rule set decides whether flows belong to a specified list of + IP networks, in which case only their network numbers are pushed. + The rules perform this test using a variety of masks, since the + network number allocations range from 16 to 24 bits in width. In + searching the flow table, the meter must distinguish between zeroes + in the address and 'don't care' bits which had been ANDed out. To + achieve this it must store SourcePeerMask values in the flow table as + well as the ANDed SourcePeerAddress values. + + In early versions of NeTraMet this problem was side-stepped by using + multiple hash tables and relying on the user to write rules which + used the same set of attributes and masks for all the flows in each + table. This was effective, but clumsy and difficult to explain. + Later versions changed to using a single hash table, and storing the + mask values for all the address attributes in each flow. + + The current version of the meter stores the address masks in + compressed form. After examining a large number of rule sets I + realised that although a rule set may have many rules, it usually has + a very small number of address masks. It is a simple matter to build + a table of address masks, and store an index to this 'mask table' + instead of a complete mask. NeTraMet's maximum number of masks is + defined at compile time, up to a maximum of 256. This allows me to + use a single byte for each mask in the flow data structure, + significantly reducing the structure's size. As well as this size + reduction, two masks can be compared by comparing their indices in + the mask table, i.e. it reduces to a single-byte comparison. + Overall, using a mask table seems to provide useful improvements in + storage efficiency and execution speed. + +2.3.5 Ignoring unwanted flow data + + As described in the Architecture document [1], every incoming packet + is tested against the current rule set by the Packet Matching Engine. + This section explains my efforts to improve NeTraMet performance on + the PC by reducing the amount of processing required by each incoming + packet. + + On the PC each incoming packet causes an interrupt, which NeTraMet + must process so as to collect information about the packet. In early + versions I used a ring buffer with 512 slots for packet headers, and + simply copied each packet's first 64 bytes into the next free slot. + The packet headers were later taken from the buffer, attribute values + were extracted from them, and the resulting 'incoming attribute + values' records were passed to the Packet Matching Engine. + + + + +Brownlee Informational [Page 10] + +RFC 2123 Traffic Flow Measurement March 1997 + + + I modified the interrupt handling code to extract the attribute + values and store them in a 'buffer slot.' This reduced the amount of + storage required in each slot, allowing more space for storing flows. + It did increase slightly the amount of processing done for each + packet interrupt, but this has not caused any problems. + + In later versions I realised that if one is only interested in + measuring IP packets, there is no point in storing (and later + processing) Novell or EtherTalk packets! It is a simple matter for + the meter to inspect a rule set and determine which Peer types are of + interest. If there are PushRule rules which test SourcePeerType (or + DestPeerType), they specify which types are of interest. If there + are no such rules, every packet type is of interest. The PC NeTraMet + has a set of Boolean variables, one for each protocol it can handle. + The values of these 'protocol' variables are determined when the + meter begins running a new rule set. For each incoming packet, the + interrupt handler determines the Peer type. If the protocol is not + of interest, no further processing is done - the packet is simply + ignored. In a similar manner, if Adjacent addresses are never tested + there is no point in copying them into the packet buffer slot. + + The overall effect of these optimisations is most noticeable for rule + files which measure IP flows on a network segment which also carries + a lot of traffic for other network protocols; this situation is + common on multiprotocol Local Area networks. On the Unix version of + NeTraMet the Operating System does all the packet interrupt + processing, and libpcap [8] delivers packet headers directly to + NeTraMet. The 'protocol' and 'adjacent address' optimisations are + still performed, at the point when NeTraMet receives the packet + headers from libpcap. + +2.3.6 Observing meter reader activity + + The Architecture document [1] explains that a flow data record must + be held in the meter until its data has been read by a meter reader. + A meter must therefore have a reliable way of deciding when flow data + has been read. The problem is complicated by the fact that there may + be more than one meter reader, and that meter readers collect their + data asynchronously. + + + + + + + + + + + + +Brownlee Informational [Page 11] + +RFC 2123 Traffic Flow Measurement March 1997 + + + Early versions of NeTraMet solved this problem by having a single MIB + variable which a meter reader could set to indicate that it was + beginning a data collection. In response to such an SNMP SET + request, NeTraMet would update its 'collectors' table. This had an + entry for each meter reader, and variables recording the start time + for the last two collections. The most recent collection might still + be in progress, but its start time provides a safe estimate of the + time when the one before it actually finished. Space used for flows + which have been idle since the penultimate collection started can be + recovered by the meter's garbage collector, as described below. + + The Meter MIB [2] specifies a more general table of meter reader + information. A meter reader wishing to collect data from a meter + must inform the meter of its intention by creating a row in the + table, then setting a LastTime variable in that row to indicate the + start of a collection. The meter handles such a SET request exactly + as described above. If there are multiple meter readers the meter + can easily find the earliest time any of them started its penultimate + collection, and may recover flows idle since then. Should a meter + reader fail, NeTraMet will eventually time out its entry in the meter + reader info table, and delete it. This avoids a situation where the + meter can't recover flows until they have been collected by several + meter readers, one of which has failed. + +2.3.7 Meter memory management + + In principle, the size of the flow table (i.e. the maximum number of + flows) could be changed dynamically. This would involve allocating + space for the flow table's new pointer array and copying the old + pointers into it. NeTraMet does not implement this. Instead the + maximum number of flows is set from the command line when it starts + execution. If no maximum is specified, a compile-time default number + is used. + + Memory for flow data structures (i.e. 'flows') is allocated + dynamically. NeTraMet requests the C run-time system for blocks of + several hundred flows, and links them into a free list. When a new + flow is needed NeTraMet gets memory space from the free list, then + searches the flow table's pointer array for an unused flow pointer. + In practice a 'last-allocated' index is used to point to the flow + table, so a simple linear search suffices. The flow index is saved + in the flow's data record, and its other attribute values are set to + zero. + + + + + + + + +Brownlee Informational [Page 12] + +RFC 2123 Traffic Flow Measurement March 1997 + + + To release a flow data record it must first be removed from any hash + list it is part of - this is straightforward since those lists are + circular. The flow's entry in the flow table pointer array is then + set to zero (NULL pointer), and its space is returned to the free + list. + + Once a flow data record is created it could continue to exist + indefinitely. In time, however, the meter would run out of space. + To deal with this problem NeTraMet uses an incremental garbage + collector to reclaim memory. + + At regular intervals specified by a 'GarbageCollectInterval' variable + the garbage collector procedure is invoked. This searches through + the flow table looking for flows which might be recovered. To + control the resources consumed by garbage collection there are limits + on the number of in-use and idle flows which the garbage collector + may inspect these are set either when NeTraMet is started (as + options on the command line) or dynamically by NeMaC (using variables + in an Enterprise MIB for NeTraMet) + + To decide whether a flow can be recovered, the garbage collector + considers how long it has been idle (no packets in either direction), + and when its data was last collected. If it has been collected by + all known meter readers since its LastTime, its memory may be + recovered. This alogrithm is implemented using a variable called + 'GarbageCollectTime,' which normally contains the meter's UpTime when + the penultimate collection (i.e. the one before last) was started. + See the section on observing meter reader activity (above) for more + details. + + Should flows not be collected often enough the meter could run out of + space. NeTraMet attempts to prevent this by having a low-priority + background process check the percentage of flows active and compare + it with the HighWaterMark MIB variable. If the percentage of active + flows is greater than the high-water mark, 'GarbageCollectTime' is + incremented by the current value of the InactivityTimeout MIB + variable. + + The Meter MIB [2] specifies that a meter should switch to using a + 'standby' rule set if the percentage of active flows rises above + HighWaterMark. In using NeTraMet to measure traffic flows to and + from the University of Auckland it has not been difficult to create + standby rules which are very similar to the 'production' rule file, + differing only in that they push much less information about flows. + This has, on several occasions, allowed the meter to continue running + for one or two days after the meter reader failed. When the meter + reader restarted, it was able to collect all the accumulated flow + data! + + + +Brownlee Informational [Page 13] + +RFC 2123 Traffic Flow Measurement March 1997 + + + The MIB also specifies that the meter should take some action when + the active flow percentage rises above its FloodMark value. If this + were not done, the meter could spend a rapidly increasing proportion + of its time garbage collecting, to the point where its ability to + respond to requests from its manager would be compromised. NeTraMet + switches to the default rule set when its FloodMark is reached. + + A potentially large number of new flows may be created when the meter + switches to a standby rule set. It is important to set a + HighWaterMark so as to allow enough flow table space for this. In + practice, a HighWaterMark of 65% and a FloodMark of 95% seem to work + well. + +2.4 Data collection + + As explained above, a meter reader wishing to collect flows begins + each collection by setting the LastTime variable in its + ReaderInfoTable row, then works its way through the flow table + collecting data. A number of algorithms can be used to examine the + flow table; these are presented below. + + The simplest approach is a linear scan of the table, reading the + LastTime variable for each row. If the read fails the row is + inactive. If it succeeds, it is of interest if its LastTime value is + greater than the time of the last collection. Although this method + is simple it is also rather slow, requiring an SNMP GET request for + every possible flow; this renders it impractical. + + Early versions of NeTraMet used two 'windows' into the flow table to + find flows which were of interest. Both windows were SNMP tables, + indexed by a variable which specified a time. A succession of + GETNEXT requests on one of these windows allowed NeMaC (the meter + reader) to find the flow indices for all flows which had been active + since the specified time. The two windows were the ActivityTime + window (which located active flows), and the CreateTime window (which + located new flows). Knowing the index of an active flow, the meter + reader can GET the values for all the attributes of interest. NeMaC + allows the user to specify which these are, rather than simply read + all the attributes. + + Having the two windows allowed NeMaC to read attributes which remain + constant - such as the flow's address attributes - when the flow is + created, but to only read attributes which change with time - such as + its packet and byte counts - during later collections. Experience + has shown, however, that many flows have rather short lifetimes; one + effect of this is that the improved efficiency of using two windows + does not result in any worthwhile improvement in collection + performance. + + + +Brownlee Informational [Page 14] + +RFC 2123 Traffic Flow Measurement March 1997 + + + The current version of the Meter MIB [2] uses a TimeFilter variable + in the flow table entries. This can be used with GETNEXT requests to + find all flows which have been active since a specified time + directly, without requiring the extra 'window' SNMP variables. It + can be combined with SNMPv2's GETBULK request to further reduce the + number of SNMP packets needed for each collection; I have yet to + implement this in NeTraMet. + + A disadvantage of using SNMP to collect data from the meter is that + SNMP packets impose a high overhead. For example, if we wish to read + an Integer32 variable (four bytes of data), it will be returned with + its object identifier, type and length, i.e. at least ten bytes of + superfluous data. One way to reduce this overhead is to use an + Opaque object to return a collection of data. NeTraMet uses this + approach to retrieve 'column activity data' from the meter, as + follows. + + Each packet of column activity data contains data values for a + specified attribute, and each value is preceded by its flow number. + The flow table can be regarded as a two-dimensional array, with a + column for each flow attribute. Column activity data objects allow + the meter reader to read columns of the flow table, so as to collect + only those attributes specified by the user. The actual + implementation is complicated by the fact that since the flow table + is read column by column, rows can become active after the first + column has been read. NeMaC reads the widest columns (those with + greatest size in bytes, e.g. PeerAddress) first, and ignores any rows + which appear in later columns. Newly active rows will, of course, be + read in the next collection. + + Using Opaque objects in this way dramatically reduces the number of + SNMP packets required to read a meter. This has proved worthwhile in + situations where the number of flows is large (for example on busy + LANs), and where the meter(s) are physically dispersed over slow WAN + links. It has the disadvantage that general-purpose MIB browsers + cannot understand the column activity variables, but this seems a + small price to pay for the improved data collection performance. + +2.5 Restarting a meter + + If a meter fails, for example because of a power failure, it will + restart and begin running rule set 1, the default rule set which is + built into the meter. Its manager must recognise that this has + happened, and respond with some suitable action. + + NeMaC allows the user to specify a 'keepalive' interval. After every + such interval NeMaC reads the meter's sysUptime and compares it with + the last sysUptime. If the new sysUptime is less than the last one, + + + +Brownlee Informational [Page 15] + +RFC 2123 Traffic Flow Measurement March 1997 + + + NeMaC decides that the meter has restarted. It downloads the meter's + backup rule set and production rule set, then requests the meter to + start running the production rule set. In normal use we use a + keepalive interval of five minutes and a collection interval of 15 + minutes. If a meter restarts, we lose up to five minutes data before + the rules sets are downloaded. + + Having the meter run the default rule set on startup is part of the + Traffic Flow Measurement Architecture [1], in keeping with the notion + that meters are very simple devices which do not have disk storage. + Since disks are now very cheap, it may be worth considering whether + the architecture should allow a meter to save its configuration + (including rule sets) on disk. + +2.6 Performance + + The PC version of the meter, NeTraMet, continually measures how much + processor time is being used. Whenever there is no incoming packet + data to process, 'dummy' packets are generated and placed in the + input buffer. These packets are processed normally by the Packet + Matching Engine; they have a PeerType of 'dummy.' The numbers of + dummy and normal packets are counted by the meter; their ratio is + used as an estimate of the processor time which is 'idle,' i.e. not + being used to process incoming packets. The Unix version is intended + to run as a process in a multiprocessing system, so it cannot busy- + wait in this way. + + The meter also collects several other performance measures; these can + be displayed on the meter console in response to keyboard requests. + + The PC meter can be used with a 10 MHz 286 machine, on which it can + handle a steady load of about 750 packets per second. On a 25 MHz + 386SX it will handle about 1250 packets per second. Users have + reported that a 40 MHz 486 can handle peaks of about 3,000 packets + per second without packet loss. The Unix meter has been tested + metering traffic on a (lightly loaded) FDDI interface; it uses about + one percent of the processor time on a SPARC 10 system running + Solaris. + +3 Writing rule sets + + The Traffic Meter provides a versatile device for measuring a user- + specified set of traffic flows, and performing useful data reduction + on them. This data reduction capability not only minimises the + volume of data to be collected by meter readers, but also simplifies + the later processing of traffic flow data. + + + + + +Brownlee Informational [Page 16] + +RFC 2123 Traffic Flow Measurement March 1997 + + + The flows of interest, and the processing to be performed, are + specified in a 'rule set' which is downloaded to the meter (NeTraMet) + by the manager (NeMaC). This section explains what is involved in + writing rule sets. + + NeTraMet is limited to metering packets observed on a network + segment. This means that for all the observed flows, Source and Dest + Type attributes (e.g. SourcePeerType and DestPeerType) have the same + value. + + The NeTraMet implementation uses single variables in its flow data + structure for AdjacentType, SourceType and TransType. Nonetheless, + the rule sets discussed below push values for both Source and Dest + Type attributes; this make sure that packet matching works properly + with the directions reversed, even for a meter which allows Source + and Dest Type values to be different. + +3.1 Rule set to observe all flows + + NeMaC reads rule sets from text files which contain the rules, the + set number which the meter (and meter reader) will identify them by, + and a 'format,' i.e. a list specifying which attributes the meter + reader should collect and write to the flow data file. The # + character indicates the start of a comment; NeMaC ignores the rest of + the line. + + SET 2 + # + RULES + # + SourcePeerType & 255 = Dummy: Ignore, 0; + Null & 0 = 0: GotoAct, Next; + # + SourcePeerType & 255 = 0: PushPkttoAct, Next; + DestPeerType & 255 = 0: PushPkttoAct, Next; + SourcePeerAddress & 255.255.255.255 = 0: PushPkttoAct, Next; + DestPeerAddress & 255.255.255.255 = 0: PushPkttoAct, Next; + SourceTransType & 255 = 0: PushPkttoAct, Next; + DestTransType & 255 = 0: PushPkttoAct, Next; + SourceTransAddress & 255.255 = 0: PushPkttoAct, Next; + DestTransAddress & 255.255 = 0: CountPkt, 0; + # + FORMAT FlowRuleSet FlowIndex FirstTime " " + SourcePeerType SourcePeerAddress DestPeerAddress " " + SourceTransType SourceTransAddress DestTransAddress " " + ToPDUs FromPDUs " " ToOctets FromOctets; + + + + + +Brownlee Informational [Page 17] + +RFC 2123 Traffic Flow Measurement March 1997 + + + The first rule tests the incoming packet's SourcePeerType to see + whether it is 'dummy.' If it is, the packet is ignored, otherwise + the next rule is executed. + + The second rule tests the Null attribute. Such a test always + succeeds, so the rule simply jumps to the action of the next rule. + (The keyword 'next' is converted by NeMaC into the number of the + following rule.) + + The third rule pushes the packet's SourcePeerType value, then jumps + to the action of the next rule. The user does not know in advance + what the value of PushPkt rules will be, which is why the value + appearing in them is always zero. The user must take care not to + write rule sets which try to perform the test in a PushPkt rule. + This is a very common error in a rule set, so NeMaC tests for it and + displays an error message. + + The following rules push a series of attribute values from the + packet, and the last rule also Counts the packet, i.e. it tells the + Packet Matching Engine (PME) that the packet has been successfully + matched. The PME responds by searching the flow table to see whether + the flow is already current (i.e. in the table), creating a new flow + data record for it should this be necessary, and incrementing its + packet and byte counters. + + Overall this rule set simply classifies the packet (i.e. decides + whether or not it is to be counted), then pushes all the Peer and + Transport attribute values for it. It makes no attempt to specify a + direction for the flow - this is left to the PME, as described in + [1]. The resulting flow data file will have each flow's source and + destination addresses in the order of the first packet the meter + observed for the flow. + +3.2 Specifying flow direction, using computed attributes + + As indicated above, the Packet Matching Engine will reliably + determine the flow, and the direction within that flow, for every + packet seen by a meter. If the rule set does not specify a direction + for the flow, the PME simply assumes that the first packet observed + for a flow is travelling forward, i.e. from source to destination. + In later analysis of the flow data, however, one is usually + interested in traffic to or from a particular source. + + One can achieve this in a simple manner by writing a rule set to + specify the source for flows. All that is required is to have rules + which succeed if the packet is travelling in the required direction, + and which execute a 'Fail' action otherwise. This is demonstrated in + the following two examples. + + + +Brownlee Informational [Page 18] + +RFC 2123 Traffic Flow Measurement March 1997 + + + (Note that early versions of NeMaC allowed 'Retry' as a synonym for + 'Fail.' The current version also allows 'NoMatch,' which seems a + better way to imply "fail, allowing PME to try a second match with + directions reversed.") + + # Count IP packets from network 130.216.0.0 + # + SourcePeerType & 255 = IP: Pushto, ip_pkt; + Null & 0 = 0: Ignore, 0; + # + ip_pkt: + SourcePeerAddress & 255.255.0.0 = 130.216.0.0: Goto c_pkt; + Null & 0 = 0: NoMatch, 0; + # + c_pkt: + SourcePeerAddress & 255.255.255.255 = 0: PushPkttoAct, Next; + DestPeerAddress & 255.255.255.255 = 0: CountPkt, 0; + + The rule labelled ip_pkt tests whether the packet came from network + 130.216. If it did not, the test fails and the following rule + executes a NoMatch action, causing the PME to retry the match with + the directions reversed. If the second match fails the packet did + not have 130.216 as an end-point, and is ignored. + + The next rule set meters IP traffic on a network segment which + connects two routers, g1 and g2. It classifies flows into three + groups - those travelling from g1 to g2, those whose source is g1 and + those whose source is g2. + + + + + + + + + + + + + + + + + + + + + + + +Brownlee Informational [Page 19] + +RFC 2123 Traffic Flow Measurement March 1997 + + + # Count IP packets between two gateways + # + # -------+-------------------+------------------+------- + # | | | + # +----+-----+ +----+-----+ +---+---+ + # | g1 | | g2 | | meter | + # +-+-+-+-+--+ +-+-+-+-+--+ +-------+ + # + SourcePeerType & 255 = IP: Pushto, ip_pkt; + Null & 0 = 0: Ignore, 0; + # + ip_pkt: + SourceAdjacentAddress & FF-FF-FF-FF-FF-FF = 00-80-48-81-0E-7C: + Goto, s1; + Null & 0 = 0: Goto, s2; + s1: + DestAdjacentAddress & FF-FF-FF-FF-FF-FF = 02-07-01-04-ED-4A + GotoAct, g3; + Null & 0 = 0: GotoAct, g1; + s2: + SourceAdjacentAddress & FF-FF-FF-FF-FF-FF = 02-07-01-04-ED-4A: + Goto, s3; + Null & 0 = 0: NoMatch, 0; + s3: + DestAdjacentAddress & FF-FF-FF-FF-FF-FF = 00-80-48-81-0E-7C: + NoMatch, 0; + Null & 0 = 0: GotoAct, g2; + # + g1: FlowClass & 255 = 1: PushtoAct, c_pkt; # From g1 + g2: FlowClass & 255 = 2: PushtoAct, c_pkt; # From g2 + g3: FlowClass & 255 = 3: PushtoAct, c_pkt; # g1 to g2 + # + c_pkt: + SourceAdjacentAddress & FF-FF-FF-FF-FF-FF = 0: + PushPkttoAct, Next; + DestAdjacentAddress & FF-FF-FF-FF-FF-FF = 0: PushPkttoAct, Next; + SourcePeerAddress & 255.255.255.255 = 0: PushPkttoAct, Next; + DestPeerAddress & 255.255.255.255 = 0: PushPkttoAct, Next; + Null & 0 = 0: Count, 0 + + The first two rules ignore non-IP packets. The next two rules Goto + s1 if the packet's source was g1, or to s2 otherwise. The rule + labelled s2 tests whether the packet's source was g2; if not a + NoMatch action is executed, allowing the PME to try the match with + the packet's direction reversed. If the match fails on the second + try the packet didn't come from (or go to) g1 or g2, and is ignored. + + + + + +Brownlee Informational [Page 20] + +RFC 2123 Traffic Flow Measurement March 1997 + + + Packets which come from g1 are tested by the rule labelled s1, and + the PME will Goto either g3 or g1. + + Packets which came from g2 are tested by the rule labelled s3. If + they are not going to g1 the PME will Goto g2. If they are going to + g1 a NoMatch action is executed - we want them counted as backward- + travelling packets for the g1-g2 flow. + + The rules at g1, g2 and g3 push the value 1, 2 or 3 from their rule + into the flow's FlowClass attribute. This value can be used by an + Analysis Application to separate the flows into the three groups of + interest. FlowClass is an example of a 'computed' attribute, i.e. + one whose value is Pushed by the PME during rule matching. + + The remaining rules Push the values of other attributes required for + later analysis, then Count the flow. + +3.3 Subroutines + + Subroutines are implemented in the PME in much the same way as in + BASIC. A subroutine body is just a sequence of statements, supported + by the GoSub and Return actions. 'GoSub' saves the PME's running + environment and jumps to the first rule of the subroutine body. + Subroutine calls may be nested as required - NeTraMet defines the + maximum nesting at compile time. 'Return n' restores the environment + and jumps to the action part of the nth rule after the Gosub, where n + is the index value from the Return rule. + + The Return action provides a way of influencing the flow of control + in a rule set, rather like a FORTRAN Computed Goto. This is one way + in which a subroutine can return a result. The other way is by + Pushing a value in either a computed attribute (as demonstrated in + the preceding section), or in a flow attribute. + + One common use for a subroutine is to test whether a packet attribute + matches one of a set of values. Such a subroutine becomes much more + useful if it can be used to test one of several attributes. The PME + architecture provides for this by using 'meter variables' to hold the + names of the attributes to be tested. The meter variables are called + V1, V2, V3, V4 and V5, and the Assign action is provided to set their + values. If, for example, we need a subroutine to test either + SourcePeerAddress or DestPeerAddress, we write its rules to test V1 + instead. Before calling the subroutine we Assign SourcePeerAddress + to V1; later tests of V1 are converted by the PME into tests on + SourcePeerAddress. Note that since meter variables may be reassigned + in a subroutine, their values are part of the environment which must + be saved by a Gosub action. + + + + +Brownlee Informational [Page 21] + +RFC 2123 Traffic Flow Measurement March 1997 + + + The following rule set demonstrates the use of a subroutine .. + + # Rule specification file to tally IP packets in three groups: + # UA to AIT, UA to elsewhere, AIT to elsewhere + # + # -------+-------------------+-----------------+-------- + # | | | + # +----+-----+ +----+-----+ +---+---+ + # | UA | | AIT | | meter | + # +-+-+-+-+--+ +-+-+-+-+--+ +-------+ + # + SourcePeerType & 255 = IP: PushtoAct, ip_pkt; + Null & 0 = 0: Ignore, 0; + # + ip_pkt: + v1 & 0 = SourcePeerAddress: AssignAct, Next; + Null & 0 = 0: Gosub, classify; + Null & 0 = 0: GotoAct, from_ua; # 1 ua + Null & 0 = 0: GotoAct, from_ait; # 2 ait + Null & 0 = 0: NoMatch, 0; # 3 other + # + from_ua: + v1 & 0 = DestPeerAddress: AssignAct, Next; + Null & 0 = 0: Gosub, classify; + Null & 0 = 0: Ignore, 0; # 1 ua-ua + Null & 0 = 0: GotoAct, ok_pkt; # 2 ua-ait + Null & 0 = 0: Gotoact, ok_pkt; # 3 ua-other + # + from_ait: + v1 & 0 = DestPeerAddress: AssignAct, Next; + Null & 0 = 0: Gosub, classify; + Null & 0 = 0: NoMatch, 0; # 1 ait-ua + Null & 0 = 0: Ignore, 0; # 2 ait-ait + Null & 0 = 0: GotoAct, ok_pkt; # 3 ait-other + # + ok_pkt: + Null & 0 = 0: Count, 0; + + The subroutine begins at the rule labelled classify (shown below). + It returns to the first, second or third rule after the invoking + Gosub rule, depending on whether the tested PeerAddress is in the UA, + AIT, or 'other' group of networks. In the listing below only one + network is tested in each of the groups - it is trivial to add more + rules (one per network) into either of the first two groups. In this + example the subroutine Pushes the network number from the packet into + the tested attribute before returning. + + + + + +Brownlee Informational [Page 22] + +RFC 2123 Traffic Flow Measurement March 1997 + + + The first invocation of classify (above) begins at the rule labelled + ip_pkt. It Assigns SourcePeerAddress to V1 then executes a Gosub + action. Classify returns to one of the three following rules. They + will Goto from_ua or from_ait if the packet came from the UA or AIT + groups, otherwise the PME will retry the match. This means that + matched flows will have a UA or AIT network as their source, and + flows between other networks will be ignored. + + The next two invocations of 'classify' test the packet's + DestPeerAddress. Packets from AIT to UA are Retried, forcing them to + be counted as AU to AIT flows. Packets from UA to UA are ignored, as + are packets from AIT to AIT. + + classify: + v1 & 255.255.0.0 = 130.216.0.0: GotoAct, ua; # ua + v1 & 255.255.0.0 = 156.62.0.0: GotoAct, ait; # ait + Null & 0 = 0: Return, 3; # other + ua: + v1 & 255.255.0.0 = 0: PushPkttoAct, Next; + Null & 0 = 0: Return, 1; + ait: + v1 & 255.255.0.0 = 0: PushPkttoAct, Next; + Null & 0 = 0: Return, 2; + +3.4 More complicated rule sets + + The next example demonstrates a way of grouping IP flows together + depending on their Transport Address, i.e. their IP port number. + Simply Pushing every flow's SourceTransAddress and DestTransAddress + would produce a large number of flows, most of which differ only in + one of their transport addresses (the one which is not a well-known + port). + + Instead we Push the well-known port number into each flow's + SourceTransAddress; its DestTransAddress will be zero by default. + + SourcePeerType & 255 = dummy: Ignore, 0; + SourcePeerType & 255 = IP: Pushto, IP_pkt; + Null & 0 = 0: GotoAct, Next; + SourcePeerType & 255 = 0: PushPkttoAct, Next; + Null & 0 = 0: Count, 0; # Count others by protocol type + # + IP_pkt: + SourceTransType & 255 = tcp: Pushto, tcp_udp; + SourceTransType & 255 = udp: Pushto, tcp_udp; + SourceTransType & 255 = icmp: CountPkt, 0; + SourceTransType & 255 = ospf: CountPkt, 0; + Null & 0 = 0: GotoAct, c_unknown; # Unknown transport type + + + +Brownlee Informational [Page 23] + +RFC 2123 Traffic Flow Measurement March 1997 + + + # + tcp_udp: + s_domain: + SourceTransAddress & 255.255 = domain: PushtoAct, c_well_known; + s_ftp: + SourceTransAddress & 255.255 = ftp: PushtoAct, c_well_known; + s_imap: + SourceTransAddress & 255.255 = 113: PushtoAct, c_well_known; + s_nfs + SourceTransAddress & 255.255 = 2049: PushtoAct, c_well_known; + s_pop: + SourceTransAddress & 255.255 = 110: PushtoAct, c_well_known; + s_smtp: + SourceTransAddress & 255.255 = smtp: PushtoAct, c_well_known; + s_telnet: + SourceTransAddress & 255.255 = telnet: PushtoAct, c_well_known; + s_www: + SourceTransAddress & 255.255 = www: PushtoAct, c_well_known; + s_xwin + SourceTransAddress & 255.255 = 6000: PushtoAct, c_well_known; + # + DestTransAddress & 255.255 = domain: GotoAct, s_domain; + DestTransAddress & 255.255 = ftp: GotoAct, s_ftp; + DestTransAddress & 255.255 = 113: GotoAct, s_imap; + DestTransAddress & 255.255 = 2049: GotoAct, s_nfs; + DestTransAddress & 255.255 = 110: GotoAct, s_pop; + DestTransAddress & 255.255 = smtp: GotoAct, s_smtp; + DestTransAddress & 255.255 = telnet: GotoAct, s_telnet; + DestTransAddress & 255.255 = www: GotoAct, s_www; + DestTransAddress & 255.255 = 6000: GotoAct, s_xwin; + # + Null & 0 = 0: GotoAct, c_unknown; # 'Unusual' port + # + c_unknown: + SourceTransType & 255 = 0: PushPkttoAct, Next; + DestTransType & 255 = 0: PushPkttoAct, Next; + SourceTransAddress & 255.255 = 0: PushPkttoAct, Next; + DestTransAddress & 255.255 = 0: CountPkt, 0; + # + c_well_known: + Null & 0 = 0: Count, 0 + # + + The first few rules ignore dummy packets, select IP packets for + further processing, and count packets for other protocols in a single + flow for each PeerType. TCP and UDP packets cause the PME to Push + their TransType and Goto tcp_udp. ICMP and OSPF packets are counted + in flows which have only their TransType Pushed. + + + +Brownlee Informational [Page 24] + +RFC 2123 Traffic Flow Measurement March 1997 + + + At tcp_udp the packets' SourceTransAddress is tested to see whether + it is included in a set of 'interesting' port numbers. If it is, the + port number is pushed from the rule into the SourceTransAddress + attribute, and the packet is counted at c_well_known. (NeMaC accepts + Pushto as a synonym for PushRuleto). + + This testing is repeated for the packet's DestTransAddress; if one of + these tests succeeds the PME Goes to the corresponding rule above and + Pushes the port number into the flow's SourceTransAddress. If these + tests fail the packet is counted at c_unknown, where all the flow's + Trans attributes are pushed. For production use more well-known + ports would need to be included in the tests above - c_unknown is + intended only for little-used exception flows! + + Note that these rules only Push a value into a flow's + SourceTransAddress, and they don't contain any NoMatch actions. They + therefore don't specify a packet's direction, and they could be used + in other rule sets to group together flows for well-known ports. + + The last example (below) meters flows from a remote router, and + demonstrates another approach to grouping well-known ports. + + SourceAdjacentAddress & FF-FF-FF-FF-FF-FF = + 00-60-3E-10-E0-A1: Goto, gateway; # tmkr2 router + DestAdjacentAddress & FF-FF-FF-FF-FF-FF = 00-60-3E-10-E0-A1: + Goto, gateway; # Source is tmkr2 + Null & 0 = 0: Ignore, 0; + # + gateway: + SourcePeerType & 255 = IP: GotoAct, IP_pkt; + Null & 0 = 0: GotoAct, Next; + SourcePeerType & 255 = 0: CountPkt, 0; + # + IP_pkt: + SourceTransType & 255 = tcp: PushRuleto, tcp_udp; + SourceTransType & 255 = udp: PushRuleto, tcp_udp; + Null & 0 = 0: GotoAct, not_wkp; # Unknown transport type + # + tcp_udp: + SourceTransAddress & FC-00 = 0: GotoAct, well_known_port; + DestTransAddress & FC-00 = 0: NoMatch, 0; + Null & 0 = 0: GotoAct, not_wkp; + # + not_wkp: + DestTransAddress & 255.255 = 0: PushPkttoAct, Next; + well_known_port: + SourcePeerType & 255 = 0: PushPkttoAct, Next; + DestPeerType & 255 = 0: PushPkttoAct, Next; + + + +Brownlee Informational [Page 25] + +RFC 2123 Traffic Flow Measurement March 1997 + + + SourcePeerAddress & 255.255.255.0 = 0: PushPkttoAct, Next; + DestPeerAddress & 255.255.255.0 = 0: PushPkttoAct, Next; + SourceTransType & 255 = 0: PushPkttoAct, Next; + DestTransType & 255 = 0: PushPkttoAct, Next; + SourceTransAddress & 255.255 = 0: CountPkt, 0; + + The first group of rules test incoming packet's AdjacentAddresses to + see whether they belong to a flow with an end point at the specified + router. Any which don't are ignored. Non-IP packets are counted in + flows which only have their PeerType Pushed; these will produce one + flow for each non-IP protocol. IP packets with TransTypes other than + UDP and TCP are counted at not_wkp, where all their address + attributes are pushed. + + The high-order six bits of SourceTransAddress for UDP and TCP packets + are compared with zero. If this succeeds their source port number is + less than 1024, so they are from a well-known port. The port number + is pushed from the rule into the flow's SourceTransAddress attribute, + and the packet is counted at well_known_port. If the test fails, it + is repeated on the packet's DestTransAddress. If the destination is + a well-known port the match is Retried, and will succeed with the + well-known port as the flow's source. + + If later analysis were to show that a high proportion of the observed + flows were from non-well-known ports, further pairs of rules could be + added to perform a test in each direction for other heavily-used + ports. + +4 Flow data files + + Although the Architecture document [1] specifies - in great detail - + how the Traffic Flow Meter works, and how a meter reader should + collect flow data from a meter, it does not say anything about how + the collected data should be stored. NeMaC uses a simple, self- + documenting file format, which has proved to be very effective in + use. + + There are two kinds of records in a flow data file: flow records and + information records. Each flow record is simply a sequence of + attribute values with separators (these can be specified in a NeMaC + rule file) or spaces between them, terminated by a newline. + + Information records all start with a cross-hatch. The file's first + record begins with ##, and identifies the file as being a file of + data from NeTraMet. It records NeMaC's parameters and the time this + collection was started. The file's second record begins with + #Format: and is a copy of the Format statement used by NeMaC to + collect the data. + + + +Brownlee Informational [Page 26] + +RFC 2123 Traffic Flow Measurement March 1997 + + + The rest of the file is a sequence of collected data sets. Each of + these starts with a #Time: record, giving the time-of-day the + collection was started, the meter name, and the range of meter times + this collection represents. These from and to times are meter + UpTimes, i.e. they are times in hundredths of seconds since the meter + commenced operation. Most analysis applications have simply used the + collection start times (which are ASCII time-of-day values), but the + from and to times could be used to convert Uptime values to time-of- + day. The flow records which comprise a data set follow the #Time + record. + +4.1 Sample flow data file + + A sample flow data file appears below. Most of the flow records have + been deleted, but lines of dots show where they were. + + ##NeTraMet v3.2. -c300 -r rules.lan -e rules.default + test_meter -i eth0 4000 flows starting at 12:31:27 Wed 1 Feb 95 + #Format: flowruleset flowindex firsttime sourcepeertype + sourcepeeraddress destpeeraddress topdus frompdus + tooctets fromoctets + #Time: 12:31:27 Wed 1 Feb 95 130.216.14.251 Flows + from 1 to 3642 + 1 2 13 5 31.32.0.0 33.34.0.0 1138 0 121824 0 + 1 3 13 2 11.12.0.0 13.14.0.0 4215 0 689711 0 + 1 4 13 7 41.42.0.0 43.34.0.0 1432 0 411712 0 + 1 5 13 6 21.22.0.0 23.24.0.0 8243 0 4338744 0 + 3 6 3560 2 130.216.14.0 130.216.3.0 0 10 0 1053 + 3 7 3560 2 130.216.14.0 130.216.76.0 59 65 4286 3796 + 3 8 3560 7 0.0.255.0 1.144.200.0 0 4 0 222 + 3 9 3560 2 130.216.14.0 130.216.14.0 118 1 32060 60 + 3 10 3560 6 130.216.0.28 130.216.0.192 782 1 344620 66 + 3 11 3560 7 0.0.255.0 0.128.113.0 0 1 0 73 + 3 12 3560 5 59.3.13.0 4.1.152.0 1 1 60 60 + 3 13 3560 7 0.128.94.0 0.129.27.0 2 2 120 158 + 3 14 3560 5 59.3.40.0 4.1.153.0 2 2 120 120 + 3 15 3560 5 0.0.0.0 4.1.153.0 0 1 0 60 + 3 16 3560 5 4.1.152.0 59.2.189.0 2 2 120 120 + . . . . . . . . . + 3 42 3560 7 0.128.42.0 0.129.34.0 0 1 0 60 + 3 43 3560 7 0.128.42.0 0.128.43.0 0 1 0 60 + 3 44 3560 7 0.128.42.0 0.128.41.0 0 1 0 60 + 3 45 3560 7 0.128.42.0 0.129.2.0 0 1 0 60 + 3 46 3560 5 4.1.152.0 59.2.208.0 2 2 120 120 + 3 47 3560 5 59.3.46.0 4.1.150.0 2 2 120 120 + 3 48 3560 5 4.1.152.0 59.2.198.0 2 2 120 120 + 3 49 3560 5 0.0.0.0 59.2.120.0 0 1 0 60 + 3 50 3664 5 4.1.152.0 59.2.214.0 0 1 0 60 + + + +Brownlee Informational [Page 27] + +RFC 2123 Traffic Flow Measurement March 1997 + + + 3 51 3664 5 0.0.0.0 4.2.142.0 0 1 0 60 + 3 52 3664 5 4.1.153.0 59.3.45.0 4 4 240 240 + #Time: 12:36:25 Wed 1 Feb 95 130.216.14.251 Flows + from 3641 to 33420 + 3 6 3560 2 130.216.14.0 130.216.3.0 0 21 0 2378 + 3 7 3560 2 130.216.14.0 130.216.76.0 9586 7148 1111118 565274 + 3 8 3560 7 0.0.255.0 1.144.200.0 0 26 0 1983 + 3 9 3560 2 130.216.14.0 130.216.14.0 10596 1 2792846 60 + 3 10 3560 6 130.216.0.28 130.216.0.192 16589 1 7878902 66 + 3 11 3560 7 0.0.255.0 0.128.113.0 0 87 0 16848 + 3 12 3560 5 59.3.13.0 4.1.152.0 20 20 1200 1200 + 3 13 3560 7 0.128.94.0 0.129.27.0 15 14 900 1144 + 3 14 3560 5 59.3.40.0 4.1.153.0 38 38 2280 2280 + 3 15 3560 5 0.0.0.0 4.1.153.0 0 30 0 1800 + 3 16 3560 5 4.1.152.0 59.2.189.0 20 20 1200 1200 + 3 17 3560 5 0.0.0.0 59.2.141.0 0 11 0 660 + . . . . . . . . . + 3 476 26162 7 0.129.113.0 0.128.37.0 0 1 0 82 + 3 477 27628 7 0.128.41.0 0.128.46.0 1 1 543 543 + 3 478 27732 7 0.128.211.0 0.128.46.0 1 1 543 543 + 3 479 31048 7 0.128.47.0 2.38.221.0 1 1 60 60 + 3 480 32717 2 202.14.100.0 130.216.76.0 0 4 0 240 + 3 481 32717 2 130.216.76.0 130.216.3.0 0 232 0 16240 + #Time: 12:41:25 Wed 1 Feb 95 130.216.14.251 Flows + from 33419 to 63384 + 3 6 3560 2 130.216.14.0 130.216.3.0 51 180 3079 138195 + 3 7 3560 2 130.216.14.0 130.216.76.0 21842 18428 2467693 1356570 + 3 8 3560 7 0.0.255.0 1.144.200.0 0 30 0 2282 + 3 9 3560 2 130.216.14.0 130.216.14.0 24980 1 5051834 60 + 3 10 3560 6 130.216.0.28 130.216.0.192 20087 1 8800070 66 + 3 11 3560 7 0.0.255.0 0.128.113.0 0 164 0 32608 + 3 12 3560 5 59.3.13.0 4.1.152.0 41 41 2460 2460 + 3 14 3560 5 59.3.40.0 4.1.153.0 82 82 4920 4920 + 3 15 3560 5 0.0.0.0 4.1.153.0 0 60 0 3600 + . . . . . . . . . + +4.2 Flow data file features + + Several features of NeMaC's flow data files (as indicated above) are + worthy of note: + + - Collection times overlap slightly between samples. This allows for + flows which were created after the collection started, and makes + sure that flows are not missed from a collection. + + + + + + + +Brownlee Informational [Page 28] + +RFC 2123 Traffic Flow Measurement March 1997 + + + - The rule set may change during a run. The above shows flows from + rule set 1 - the default set - in the first collection, followed by + the first flows created by rule set 3 (which has just been + downloaded by NeMaC). + + - FlowIndexes may be reused by the meter once their flows have been + recovered by the garbage collector. The combination of + FlowRuleSet, FlowIndex and StartTime are needed to identify a flow + uniquely. + + - Packet and Byte counters are 32-bit unsigned integers, and are + never reset by the meter. Computing the counts occurring within a + collection interval requires taking the difference between the + collected count and its value when the flow was last collected. + Note that counter wrap-around can be allowed for by simply + performing an unsigned subtraction and ignoring any carry. + + - In the sample flow data file above I have used double spaces as + separators between the flow identifiers, peer addresses, pdu counts + and packet counts. + + - The format of addresses in the flow data file depends on the type + of address. NeMaC always displays Adjacent addresses as six hex + bytes separated by hyphens, and Transport addresses as (16-bit) + integers. The format of a Peer address depends on its PeerType, + e.g. dotted decimal for IP. To facilitate this NeMaC needs to know + the PeerType for each flow; the user must request NeMaC to collect + it. + +4.3 Terminating and restarting meter reading + + When NeMaC first starts collecting from a meter, it reads the flow + data for all active flows. This provides a starting point for + analysis applications to compute the counts between successive + collections. + + From time to time the user needs to terminate a flow data file and + begin a new one. For example, a user might need to generate a + separate file for each day of metering. NeMaC provides for this by + closing the file after each collection, then opening it and appending + the data from the next collection. To terminate a file the user + simply renames it. The Unix system will effect the name change + either immediately (if the file was closed) or as soon as the current + collection is complete (and the file is closed). + + When NeMaC begins its next collection it observes that the file has + disappeared, so it creates a new one and writes the # header records + before writing the collected data. + + + +Brownlee Informational [Page 29] + +RFC 2123 Traffic Flow Measurement March 1997 + + + There is one aspect of the above which requires some care on the + user's part. The last data set in a file is not duplicated as the + first data set of the next file. In other words, analysis + applications must either look ahead at the first data set of the next + file, or begin by reading the last data set of the previous file. If + they fail to do this they will loose one collection's worth of flow + data at each change of file. + +5 Analysis applications + + Most analysis applications will be unique, taking data produced by a + locally-developed rule set and producing reports to satisfy specific + local requirements. The NeTraMet distribution files include three + applications which are of general use, as follows: + + - fd_filter computes data rates, i.e. the differences between + successive data sets in a flow data file. It also allows the user + to assign a 'tag' number to each flow; these are 'computed' + attributes similar to FlowClass and FlowKind - the only difference + is that they are computed from the collected data sets. + + - fd_extract takes 'tagged' files from fd_filter and produces simple + 'column list' files for use by other programs. One common use for + fd_extract is to produce time-series data files which can be plotted + by utilities like GNUPlot. + + - nm_rc is a 'remote console' for a NeTraMet meter. It is a slightly + simplified version of NeMaC combined with fd_filter. It can be used + to monitor any meter, and will display (as lines of text + characters) information about the n busiest flows observed during + each collection interval. + + - nifty is a traffic flow analyser, which (like nm_rc) displays data + from a NeTraMet meter. nifty is an X/Motif application, which + produces displays like 'Packet rate (pps) vs Flow lifetime + (minutes),' so as to highlight those flows which are 'interesting.' + + These applications are useful in themselves, and they provide a good + starting point for users who wish to write their own analysis + applications. + + + + + + + + + + + +Brownlee Informational [Page 30] + +RFC 2123 Traffic Flow Measurement March 1997 + + +6 Using NeTraMet in a measurement system + + This section gives a brief summary of the steps involved in setting + up a traffic measurement system using NeTraMet. These are: + + - Decide what is to be measured. One good way to approach this is to + specify exactly which flows are to be measured, and what reports + will be required. Specifying the flows should make it obvious + where meters will have to be placed so that the flows can be + observed, whether PCs will be adequate for the task, etc.. + + - Install meters. As well as actually placing the meter hosts this + includes making sure that they are configured correctly, with + appropriate IP addresses, SNMP community strings, etc. + + - Develop the rule set (and a standby rule set). The degree of + difficulty here depends on how much is known in advance about the + traffic. One possible approach is to start with the meter default + rule set and measure how much traffic there is for each PeerType. + (This is a good way to verify that NeTraMet and NeMaC are working + properly). You can now add rules so as to increase the granularity + of the flows; this will of course increase the number of flows to + be collected, and force the meter's garbage collector to work + harder. Another approach is to try a rule set with very fine + granularity (i.e. one which Pushes all the address attributes), + then observing how many flows are collected every few minutes. + + - Develop a strategy for controlling meter reader. This means + setting the meter's maximum number of flows, the collection + interval, how breaks between flow data files will be handled, how + often NeMaC should check that the meter is running, etc. + + - Develop application(s) to process the collected flow data and + produce the required files and reports. + + - Test run. Monitor the system, then refine the rule sets and meter + reading strategy until the overall system performance is + satisfactory. + + This process can take quite a long time, but the overall result is + well worth the effort. + +6.1 Examples of NeTraMet in production use + + At the University of Auckland we run two sets of meters. One of + these measures the traffic entering and leaving our University + network, and generates usage reports for all our Internet users. + This has been in production since early 1994. + + + +Brownlee Informational [Page 31] + +RFC 2123 Traffic Flow Measurement March 1997 + + + The other set consists of meters which are distributed at + Universities throughout New Zealand. They provide continuous traffic + flow measurements at five-minute intervals for all the links making + up the Universities' network (Kawaihiko); this system has been in + production since January 1996, and has already proved very useful in + planning the network's development. + + The Kawaihiko Network provides IP connectivity for the New Zealand + Universities. They are linked via a Frame Relay cloud, using a + partial mesh of permanent virtual circuits. There is a NeTraMet + meter at each site, metering inward and outward traffic. All the + meters are managed from Auckland, and they all run copies of the same + rule set. + + The rule set has about 650 rules, most of which are in a single + subroutine which classifies PeerAddresses into three categories - + 'Kawaihiko network,' 'other New Zealand network' and 'non-New Zealand + network.' Inside New Zealand IP addresses lie within six CIDR + blocks, and there are about four hundred older networks which have + addresses outside those blocks. The rules are arranged in groups by + subnet size, i.e. all the /24 networks are tested first, then the /23 + networks, etc, finishing with the /16 networks. This means that + although there are about 600 networks, any PeerAddress can be + classified with only nine tests. + + The Kawaihiko rule set classifies flows, using computed attributes to + indicate the network 'kind' (Kawaihiko / New Zealand / international) + for each flow's SourcePeerAddress and DestPeerAddress, and to + indicate whether the flow is a 'network news' flow or not. + + Flow data is collected from all of the meters every five minutes, and + is used to produce weekly reports, as follows: + + - Traffic Plots. Plots of the 5-minute traffic rates for each site, + showing international traffic in and out, news traffic in and out, + and total traffic in and out of the site. + + - Traffic Matrices. Two of these are produced, one for news traffic, + the other for total traffic. They show the traffic rates from + every site (including 'other New Zealand' and 'international') to + every other site. The mean, third quartile and maximum are printed + for every cell in the matrices. + + + + + + + + + +Brownlee Informational [Page 32] + +RFC 2123 Traffic Flow Measurement March 1997 + + +7 Acknowledgments + + This memo documents the implementation work on traffic flow + measurement here at the University of Auckland. Many of my + University colleagues have contributed significantly to this work, + especially Russell Fulton (who developed the rules sets, Perl scripts + and Cron jobs which produce our traffic usage reports automatically + week after week) and John White (for his patient help in documenting + the project). + +8 References + + [1] Brownlee, N., Mills, C., and G. Ruth, "Traffic Flow + Measurement: Architecture", RFC 2063, The University of Auckland, + Bolt Beranek and Newman Inc., GTE Laboratories, Inc, January 1997. + + [2] Brownlee, N., "Traffic Flow Measurement: Meter MIB", + RFC 2064, The University of Auckland, January 1997. + + [3] CRYNWR Packer Drivers distribution site: + http://www.crynwr.com/ + + [4] Case J., McCloghrie K., Rose M., and Waldbusser S., + "Structure of Management Information for version 2 of the + Simple Network Managemenet Protocol", RFC 1902, SNMP Research + Inc., Hughes LAN Systems, Dover Beach Consulting, Carnegie + Mellon University, April 1993. + + [5] IBM Corporation, "IBM PC Technical Reference Manual," 1984. + + [6] Waterloo TCP distribution site: + http://mvmpc9.ciw.uni-karlsruhe.de:80/d:/public/tcp_ip/wattcp + + [7] CMU SNMP distribution site: + ftp://lancaster.andrew.cmu.edu/pub/snmp-dist + + [8] libpcap distribution site: + ftp://ftp.ee.lbl.gov/libpcap-*.tar.gz + + + + + + + + + + + + + +Brownlee Informational [Page 33] + +RFC 2123 Traffic Flow Measurement March 1997 + + +9 Security Considerations + + Security issues are not discussed in detail in this document. The + meter's management and collection protocols are responsible for + providing sufficient data integrity and confidentiality. + +10 Author's Address + + Nevil Brownlee + The University of Auckland + + Phone: +64 9 373 7599 x8941 + Email: n.brownlee@auckland.ac.nz + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Brownlee Informational [Page 34] + |