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12 13 RFC 5474
INTERNET-DRAFT Nick Duffield (Editor)
draft-ietf-psamp-framework-01.txt Albert Greenberg
November 2002 Matthias Grossglauser
Expires: May 2003 Jennifer Rexford
AT&T Labs - Research
Derek Chiou
Avici Systems
Peram Marimuthu
Ganesh Sadasivan
Cisco Systems
A Framework for Passive Packet Measurement
Copyright (C) The Internet Society (2002). All Rights Reserved.
This document is an Internet-Draft and is in full conformance with
all provisions of Section 10 of RFC2026.
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Abstract
A wide range of traffic engineering and troubleshooting tasks rely
on reliable, timely, and detailed traffic measurements. We describe
a framework for passive packet measurement that is (a) general
enough to serve as the basis for a wide range of operational tasks,
and (b) needs only a small set of packet selection operations that
facilitate ubiquitous deployment in router interfaces or dedicated
measurement devices, even at very high speeds.
Comments on this document should be addressed to the PSAMP WG
mailing list: psamp@ops.ietf.org
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0 Contents
1 Motivation ................................................. 3
2 Requirements ............................................... 3
3 Elements, Terminology, and Architecture .................... 5
4 Packet Selection Operations ................................ 7
4.1 Filtering .............................................. 7
4.2 Sampling ............................................... 7
4.3 Hashing ................................................. 7
4.4 Selection According to Packet Treatment ................ 8
4.5 Classification and Relation of Selection Operations .... 9
4.6 Proposal on Requirements for Selection Operations ...... 9
5 Reporting .................................................. 9
6 Export and Congestion Avoidance ............................ 10
6.1 Collector Destination .................................. 10
6.2 Local Export ........................................... 10
6.3 Reliable vs. Unreliable Transport ..................... 11
6.4 Limiting Delay in Exporting Measurement Packets ........ 11
6.5 Configurable Export Rate Limit ......................... 11
6.6 Congestion-aware Unreliable Transport .................. 12
6.7 Collector-based Rate Reconfiguration ................... 12
6.7.1 Changing the Export Rate and Other Rates ........... 12
6.7.2 Notions of Fairness ................................ 13
6.7.3 Behavior Under Overload and Failure ................ 13
7 Parallel Measurement Processes ............................. 13
8 Configuration and Management ............................... 14
9 Feasibility and Complexity ................................. 14
9.1 Feasibility ............ ............................... 14
9.1.1 Filtering .......................................... 14
9.1.2 Sampling ........................................... 14
9.1.3 Hashing ............................................ 15
9.1.4 Reporting .......................................... 15
9.1.5 Export ............................................. 15
9.2 Potential Hardware Complexity .......................... 15
10 Applications .............................................. 16
10.1 Baseline Measurement and Drill Down ................... 16
10.2 Customer Performance .................................. 17
10.3 Troubleshooting ....................................... 17
11 References ................................................ 19
12 Authors' Addresses ........................................ 20
13 Intellectual Property Statement ........................... 21
14 Full Copyright Statement .................................. 21
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1 Motivation
This document describes a framework in which to define a standard
set of capabilities for network elements to sample subsets of
packets by statistical and other methods. The framework will
accommodate future work to (i) specify a set of selection
operations by which packets are sampled (ii) specify the
information that is to be made available for reporting on sampled
packets; (iii) describe protocols by which information on sampled
packets is reported to applications; (iv) describe protocols by
which packet selection and reporting are configured.
The motivation to standardize these capabilities comes from the
need for measurement-based support for network management and
control across multivendor domains. This requires domain wide
consistency in the types of selection schemes available, the manner
in which the resulting measurements are presented, and
consequently, consistency of the interpretation that can be put on
them.
The capabilities are positioned as suppliers of packet samples to
higher level consumers, including both remote collectors and
applications, and on board measurement-based applications. Indeed,
development of the standards within the framework described here
should be open to influence by the requirements of standards in
related IETF WGs, for example, IP Performance Metrics (IPPM)
[PAMM98] and Internet Traffic Engineering (TEWG) [LCTV02].
Conversely, we expect that aspects of this framework not
specifically concerned with the central issue of packet selection
may be able to leverage work in other WGs. Potential examples are
the format and export of measurement reports, which may leverage
the work in IP Flow Information Export (IPFIX) [QZCZCN02], and work
in congestion aware unreliable transport in the Datagram Congestion
Control Protocol (DCCP) [FHK02].
2 Requirements
The broad requirements for the measurement capabilities are:
* Ubiquity: The capabilities must be simple enough to be
implemented ubiquitously at maximal line rate. In particular,
they must involve only minimal per-packet processing and
require only minimal additional state. Capabilities should not
be tightly integrated with other packet control actions such as
policing, marking, shaping, and queueing.
* Applicability: the set of selection operations must be rich
enough to support a range of existing and emerging measurement
based applications and protocols. The standard will have to
find a workable trade-off between the range of traffic
engineering applications and operational tasks it enables, and
the complexity of the set of capabilities.
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* Timeliness: reports on selected packets should be made available
to the collector quickly enough to support real time
applications.
* Transparency: allow transparent interpretation of measurements as
communicated by PSAMP reporting, without need to obtain
additional information from the measuring device.
* Robustness: allow robust interpretation of measurements with
respect to reports missing due to loss, e.g. in transport, or
omission at the measurement device. Inclusion in reporting of
information enabling accuracy of measurements to be determined.
* Privacy: selection of the content of packet reports will be
cognizant of privacy and anonymity issues while being
responsive to the needs of measurement applications, and in
accordance with RFC 2804. Full packet capture of arbitrary
packet streams is explicitly out of scope.
* Faithfulness: all reported quantities that relate to the packet
treatment must reflect the router state and configuration
encountered by the packet in the PSAMP device.
* Configuration: ease of configuration of sampling and export
parameters, e.g. for automated remote reconfiguration in
response to measurements.
* Security: the use of secure means of configuration and reporting,
and robustness of packet selection w.r.t. attempts to evade
measurement.
* Extensibility: to allow for additional packet selection
operations to support future applications.
* Flexibility: to support measurement of packets using different
network protocols or encapsulation layers (e.g. IPv4, IPv6,
MPLS, etc), and under packet encryption.
* Parallel measurements: support multiple independent measurements
at the same device, each possibly with different selection,
reporting and export configuration.
* Congestion Avoidance: export of a report stream across a network
must be congestion avoiding in compliance with RFC 2914.
Reuse of existing protocols will be encouraged provided the
protocol capabilities are compatible with the above requirements.
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3 Elements, Terminology, and Architecture
This section defines the basic elements of the PSAMP framework.
* PSAMP Device: a device hosting at least an observation point and
a measurement process.
* Observation Point: The observation point is a location in the
network where packets can be observed. Examples are, a line
to which a probe is attached, a shared medium, such as an
Ethernet-based LAN, a single port of a router, or set of
interfaces (physical or logical) of a router, an embedded
measurement subsystem within an interface.
* Measurement Process: a packet measurement process comprising the
following: a selection process, a reporting process, and an
export process.
* Selection Process: A selection process selects packets for
reporting at an observation point. The inputs to the selection
process are the packets observed at the observation point
(including packet encapsulation headers), information derived
from the packets' treatment at the observation point, and
selection state that may be maintained by the observation
point. Selection is accomplished through operating on these
inputs with one or more selection operations.
* Selection Operation: A configurable packet selection operation.
It takes as input the selection process input for a single
packet. The output is a binary outcome of whether or not the
packet was sampled. Selection operations may also change the
selection state.
* Selection State: the observation point may maintain state
information for use by the reporting process, and/or by
multiple selection operations, either on the same packet, or on
different packets. Examples include counters, timestamps,
iterators for pseudorandom number generators, calculated hash
values, and indicators of whether a packet was selected by a
given selection operation.
* Composite Selection Operation: a selection operation that is
expressed as a combination of other selection operations. A
packet deemed selected by the composite operation if it is
selected by all its constituent selection operations.
* Reporting Process: the creation of a report stream of information
on packets selected by a selection process, in preparation for
export. The input to a reporting process comprises that
information available to a selection process, for the selected
packets. The report stream contains two distinguished types of
information: packet reports, and report interpretation.
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* Packet Reports: a configurable subset of the per packet input to
the reporting process.
* Report Interpretation: subsidiary information relating to, and
used for the interpretation the reports on, one or more
packets. Examples include counters, and configuration parameters
of the PSAMP device, and the selection and reporting process.
* Export Process: sends the output of the reporting process
from the PSAMP device to one or more collectors.
* Collector: a collector receives a report stream exported by one
or more measurement processes. The collector may or may not be
co-located with the PSAMP device.
* Measurement packets: report interpretation and/or one or more
packet reports are bundled by the export process into a
measurement packet for export to a collector.
* Parallel Measurement Processes: a given PSAMP device may host
multiple independent measurement processes, each with
potentially different constituent selection, reporting and
export processes, and destination collectors. The parallel
processes may or may not use derive their input from the same
observation point.
The various possibilities for the high level architecture of these
elements is as follows. Note in the last case: the PSAMP device may
also be a collector.
+---------------------+ +------------------+
|PSAMP Device(1) | | Collector(1) |
|[Obsv. Point(s)] | | |
|[Meas. Process(1)]<--+---------------->| |
|[Meas. Process(2)]<--+-----------+---->| |
|[Meas. Process(3)]<--+--------+ | | |
+---------------------+ | | +------------------+
| |
+---------------------+ | | +------------------+
|PSAMP Device(2) | | +---->| Collector(2) |
|[Obsv. Point(s)] | +------->| |
|[Meas. Process(4)]<--+---------------->| |
+---------------------+ +------------------+
+---------------------+ +------------------+
|PSAMP Device(3) | | Collector(3) |
|[Obsv. Point(s)] | | |
|[Meas. Process(5)]<--+---------------->| |
|[Meas. Process(6)]<--+---\ +------------------+
|Collector(4)<--------+---/
+---------------------+
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4 Packet Selection Operations
The function of packet selection is to select a subset out of the
stream of all packets. Selection may be used to select a subset of
packets of interest based on their content, and/or to reduce the
rate of packets into the measurement flow regardless of
content. This section details some candidate operations for
standardization. No restriction on the allowed combination of these
into composite selection operations is imposed in this
document. Packet selection techniques are discussed in [ZMR02].
4.1 Filtering
Filtering can be accomplished by applying deterministic operations,
such as match/mask, to any combination of bit positions in the
generic selection function input. Higher level interfaces to the
match/mask operations may be used to specify mask and matches for
particular fields, for example, for IP addresses and/or TCP/UDP
port numbers.
4.2 Sampling
In current practice, sampling has been performed using particular
algorithms, e.g., (i) pseudorandomly independent sampling with
probability 1/N; (ii) periodic sampling of every Nth packet. The
aim is to select packets representatively in conformance with some
desired probabilistic selection law. Examples of selection laws are
selecting packets (i) with long term probability 1/N; (ii)
independently with probability 1/N; (iii) n out of every m packets
independently; (iv) by importance, non-uniformly according to field
contents, e.g. sample larger packets or certain protocols more
frequently. A given sampling algorithm will reproduce the selection
law if the packets under observation conform to a certain
probabilistic content law. Examples of content laws are (i)
correlations between contents of different packets decay at a
specified rate; (ii) the contents of certain complimentary
subfields are significantly variable and essentially uncorrelated.
It follows that the extent to which sampling algorithms should be
realized as distinct selection operations depends on the functional
requirements, as expressed by the selection laws that are desired
and the content laws that one is prepared to assume. For example,
under the content law that correlations between packet contents
vanish for packets separated by at least N-1 positions in the
packet stream, then sampling every Nth packet periodically yields
the same selection law as sampling independently with probability
1/N. With a weaker content law (i.e. admitting stronger
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correlations between packets), then only the long term selection
probabilities may be 1/N. One task for the work under the PSAMP
framework will be to decide the appropriate level of functional
granularity, e.g. whether to distinguish periodic from pseudorandom
sampling as a packet selection operations, or to regard them only
as different possible implementations of the same packet selection
operation.
Sampling at full line rate, i.e. with probability 1, is not
excluded in principle, although resource constraints may not
support it in practice.
4.3 Hashing
A hashing function operates on the selection function input for a
packet, and associates the resulting hash with the packet. Bit
positions can be excluded from the input to the hashing function by
masking. This ability would be used, for example, by applications
that require the hash to be independent on packet header fields,
such as TTL or header CRC, that are mutable on its passage through
the network.
Packets may be selected by filtering on the hash value, this
regarded as part of the selection state. Although hashing and
filtering are deterministic operations, a good choice of the hash
function and its inputs should yield a selection law that is almost
indistinguishable from independent sampling (for a given subfield
of the packet) given an appropriate content law (that the contents
of complimentary subfields are sufficiently uncorrelated and
variable).
At the application level, hash-based sampling is of interest since
using the same hash functions at different PSAMP devices satisfies
a functional requirement that the same sampling decision be made on
a given packet observed at different devices; in [DuGr01] this is
called Trajectory Sampling. It enables reconstruction of the
network paths followed by individual packets, from packet reports
exported from different PSAMP devices. In this application, a
second distinct hash, called the label hash, may be calculated for
selected packets in order to identify them at the collector. PSAMP
devices are expected to be able to use a more complex hash for this
second purpose, since it is only applied to the reduced set of
selected packets.
Calculating and reporting a set of hashes for all packets
(i.e. without selecting a subset) would be required in order to
support some packet tracing applications; see [SPSJTKS01].
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4.4 Selection According to Packet Treatment
Router architectural considerations may preclude some information
concerning the packet treatment, e.g routing state, being available
at line rate for selection of packets. However, if selection not
based on routing state has reduced down from line rate,
subselection based on routing state may be feasible.
4.5 Classification and Relation of Selection Operations
From the above examples, it is clear that notions of sampling,
filtering and hashing are not distinct. For example: (i) sampling
can be accomplished by hashing and filtering; and (ii) since a
sampling selection law can depend on packet content, filtering can
be regarded as a degenerate case of sampling, although it does not
appear useful to do so. For this reason, it is likely to be more
fruitful to standardize selection operations according to agreed
functional requirements, than to strive to define a non-overlapping
classification of selection operations.
4.6 Proposal on Requirements for Selection Operations
Section 10 describes potential PSAMP applications. These would be
supported by the following set of selection operations:
(i) filtering by match/mask to support drill down
(ii) hash-based sampling to support Trajectory Sampling
(iii) independent sampling method to support widespread baselineing
5 Reporting
Information eligible for inclusion in packet reports includes (i)
the packet content itself (including encapsulating headers); (ii)
information relating to the packet treatment: incoming and outgoing
interfaces, subinterfaces and channel identifiers, routing state
applied to or derived from the packet e.g. next hop IP address,
routing prefixes, source and destination AS numbers; (iii)
selection state associated with the packet, e.g. timestamps,
counters, hash values.
In order to satisfy the requirement of ubiquity, it may be
necessary to admit different levels of reporting. Concerning the
packet content: some devices may not have the resource capacity or
functionality to identify all fields within a packet. Concerning
packet treatment: routing state is unlikely to be available on
devices that do not route. At a minimum, all PSAMP devices must
support simple reporting of packet content, specifically of some
number of bytes contiguous packet bytes, as measured from an
offset. In this style of reporting, the burden of interpretation is
placed at the collector or applications that it supplies. More
detailed reporting, by fields of specific protocols, is desirable
where feasible.
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Information for use in report interpretation includes (i)
configuration parameters of the selectors of the packets reported
on; (ii) format of the packet reports (iii) configuration
parameters and state information of the network element; (iv)
quantities (e.g. sequence numbers) that enable collectors and
applications to infer attained packet sampling rates, detect
loss during selection, report loss in transmission, and correct for
information missing from the packet report stream; (v) indication
of the inherent accuracy of the reported quantities, e.g., of
timestamps.
The requirements for robustness and transparency are motivations
for including report interpretation in the report stream. Inclusion
makes the report stream self-defining. The PSAMP framework
excludes reliance on an alternative model in which interpretation
is recovered out of band. This latter approach is not robust with
respect to undocumented changes in selection configuration, and
leaves an architectural hostage for network management systems to
coherently manage both configuration and data collection.
It is not envisaged that all report interpretation be included in
every report. Many of the quantities listed above are expected to
be relatively static; they could be communicated periodically, and
upon change.
To conserve network bandwidth and resources at the collector, the
PSAMP device may compress the measurement records before export.
Compression should be quite effective since the sampled packets may
share many fields in common, e.g. if a filter focuses on packets
with certain values in particular header fields. Using compression,
however, could impact the timeliness of reports. Any consequent
delay should not violate the timeliness requirement for
availability of packet reports at the collector.
6 Export and Congestion Avoidance
6.1 Collector Destination
At least when exporting to a remote collector, the export process
is configured to transmit to the collector, as identified by IP
address and port number.
6.2 Local Export
The report stream may be directly exported to on-board measurement
based applications, for example those that for composite statistics
from more than one packet. Local export may be presented through an
interface direct to the higher level applications, i.e., without
employing the transport used for off-board export.
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6.3 Reliable vs. Unreliable Transport
The export of the report stream does not does require reliable
export. On the contrary, retransmission of lost measurement packets
consumes additional network resources and require maintenance of
state by the export process. The PSAMP device would have to be
addressable, and able to receive and process acknowledgments, and to
store unacknowledged data. These requirements would be a
significant impediment to having ubiquitous support PSAMP.
Instead, it is proposed that PSAMP devices support an unreliable
export mechanism. Sequence numbers on the measurement packets would
indicate when loss has occurred, and the analysis of the collected
measurement data can account for this loss. In some sense, packet
loss becomes another form of sampling (albeit a less desirable, and
less controlled, form of sampling).
6.4 Limiting Delay in Exporting Measurement Packets
The device may queue the report stream in order to export multiple
records in a single measurement. Any consequent delay should not
violate the timeliness requirement availability of packet reports
at the collector.
6.5 Configurable Export Rate Limit
The export process must be able to limit its export rate; otherwise
it could overload the network and/or the collector. (Note this
problem would be exacerbated if using reliable transport mode,
since the PSAMP device would retransmit any lost packets,
thereby imposing an additional load on the network).
At times, the device may generate new records faster than the
allowed export rate. In this situation, the device should discard
the excess records rather than transmitting them to the collection
system. The device may record information (such as sequence
numbers, or packet and byte counter values accumulated at the
inputs and outputs of a packet selector) to aid the collection
system in compensating for the missing data in any subsequent
analysis.
The export rate must be configurable per export process. Note that
since congestion loss can occur at any link on the export path, it
is not sufficient to limit rate simply as a function of the
bandwidth of the interface out of which export takes place.
A candidate for implementation of rate limiting is the leaky
bucket, with tokens corresponding e.g. to bytes or packets.
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6.6 Congestion-aware Unreliable Transport
Exported measurement traffic competes for resources with other
Internet transfers. Congestion-aware export is important to ensure
that the measurement records do not overwhelm the capacity of the
network or unduly degrade the performance of other applications,
while making good use of available bandwidth resources.
The PSAMP WG will evaluate (at least) the following alternatives
for congestion aware unreliable transport:
(i) protocols under development, including the Datagram Congestion
Control Protocol (DCCP); see [FHK02]
(ii) protocols adopted in the future by the IPFIX WG,
(iii) collector-based rate reconfiguration, as now described.
6.7 Collector-based Rate Reconfiguration
Since collector-based rate reconfiguration is a new proposal, this
draft will discuss it in some detail.
The collector can detect congestion loss along the path from the
PSAMP device through lost packets, manifest as gaps in the sequence
numbers, or the absence of packets for a period of time. The server
can run an appropriate congestion-control algorithm to compute a
new export rate limit, then reconfigure the PSAMP device with the
new rate. This is an attractive alternative to requiring the PSAMP
device to receive acknowledgment packets. Implementing the
congestion control algorithm in the collection server has the added
advantages of flexibility in adapting the sending rate and the
ability to incorporate new congestion-control algorithms as they
become available.
6.7.1 Changing the Export Rate and Other Rates
Forcing the PSAMP device to discard excess records is an effective
control under short term congestion. Alternatively, the device
could be reconfigured to select fewer packets, and/or send smaller
reports on each selected packet. This may be a more appropriate
reaction to long-term congestion. In some cases, a collection
server may receive measurement records from more than one device,
and could decide to reduce the export or other rates at one device
rather than another, in order to prioritize the measurement data.
This type of flexibility is valuable for network operators that
collect measurement data from multiple locations to drive multiple
applications.
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6.7.2 Notions of Fairness
In some cases, it may be reasonable to allow the collection server
to have flexibility in deciding how aggressively to respond to
congestion. For example, the PSAMP device and the collection
server may have a very small round-trip time relative to other
traffic. Conventional TCP-friendly congestion control would
allocate a very large share of the bandwidth to this traffic.
Instead, the collection server could apply an algorithm that reacts
more aggressively to congestion to give a larger share of the
bandwidth to other traffic (with larger RTTs). In other cases, the
measurement records may require a larger share of the bandwidth
than other flows. For example, consider a link that carries tens
of thousands of flows, including some non TCP-friendly DoS attack
traffic. Restricting the PSAMP traffic to a fair share allocation
may be too restrictive, and might limit the collection of the data
necessary to diagnose the DoS attack. In order to maintain report
collection during periods of congestion, PSAMP report streams may
claim more than a fair share of link bandwidth, provided the number
of report streams in competition with fair sharing traffic is
limited. The collection server could also employ policies that
allocate bandwidth in certain proportions amongst different
measurement processes.
6.7.3 Behavior Under Overload and Failure
The congestion control algorithm has to be robust to severe
overload or complete loss of connectivity between the device and
the collection system, and also to the failure of the device or the
collection system. For example, in a scenario where the collection
system is unable to reconfigure the export rate because of loss of
reverse (collection system to device) connectivity, it is desirable
that the device reduce the export rate automatically. Similarly, if
no measurement reports reach the collection system because of loss
of forward connectivity, the collection system should not react to
this by increasing the export rate. This problem may be solved
through periodic heartbeat packets in both directions (i.e.,
measurement reports in the forward direction, configuration refresh
messages in the reverse direction). This allows each side to
detect a loss in connectivity or outright failure and to react
appropriately.
7 Parallel Measurement Processes
Because of the increasing number of distinct measurement
applications, with varying requirements, it is desirable to set up
parallel measurement processes on a stream of packets. Each
process should consist of independently-configurable selection,
reporting and export processes.
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Each of the parallel measurement processes should be, as far as
possible, independent. However, resource constraints may prevent
complete reporting on a packet selected by multiple selection
processes. In this case, reporting for the packet must be complete
for at least one information flow; other information flows need
only report that they selected the packet. The priority amongst
information flows to report packets must be configurable.
It is not proposed to standardize the number of parallel
measurement processes available.
8 Configuration and Management
A key requirement for PSAMP is the easy reconfiguration of
parameters the parameters of the measurement process: those for
selection, packet reports and export. Examples are (i) support of
measurement based applications that want to drill-down on traffic
detail in real-time; (ii) collector-based rate reconfiguration.
To facilitate reconfiguration and retrieval of parameters, they are
to reside in a Management Information Base (MIB). CLI and SNMP
access to these parameters must be available.
9 Feasibility and Complexity
In order for PSAMP to be supported across the entire spectrum of
networking equipment, it must be simple and inexpensive to
implement. One can envision easy-to-implement instances of the
mechanisms described within this draft. Thus, for that subset of
instances, it should be straightforward for virtually all system
vendors to include them within their products. Indeed, sampling and
filtering operations are already realized in available equipment.
Here we give some specific arguments to demonstrate feasibility and
comment on the complexity of hardware implementations. We stress
here that the point of these arguments is not to favor or recommend
any particular implementation, or to suggest a path for
standardization, but rather to demonstrate that the set of possible
implementations is not empty.
9.1 Feasibility
9.1.1 Filtering
Filtering consists of a small number of mask (bit-wise logical),
comparison and range (greater than) operations. Implementation of
at least a small number of such operations is straightforward.
9.1.2 Sampling
Sampling based on either counters (counter set, decrement, test for
equal to zero) or range matching on the hash of a packet (greater
than) are also straightforward given a small number of them.
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9.1.3 Hashing
Hashing functions vary greatly in complexity. Execution of a small
number of sufficient simple hash functions is implementable at line
rate.
9.1.4 Reporting
The simplest packet report would duplicate the first n bytes of the
packet. However, such an uncompressed format may tax the bandwidth
capabilities of the PSAMP device for high sampling rates; reporting
selected fields would save on bandwidth within the PSAMP
device. Thus there is a trade-off between simplicity and bandwidth
limitations within the PSAMP device.
9.1.5 Export
Ease of exporting measurement packets depends on the system
architecture. Most systems should be able to support PSAMP export
by insertion of measurement packets, even through the software
path.
9.2 Potential Hardware Complexity
We now comment on the complexity of possible hardware
implementations. Achieving low constants for performance while
minimizing hardware resources is, of course, a challenge,
especially at very high clock frequencies. Most of these
operations, however, are very basic and their implementations very
well understood; in fact, the average ASIC designer simply uses
canned library instances of these operations rather then design
them from scratch. In addition, networking equipment generally does
not need to run at the fastest clock rates, further reducing the
effort required to get reasonably efficient implementations.
Simple bit-wise logical operations are easy to implement in
hardware. Such operations (NAND/NOR/XNOR/NOT) directly translate
to four-transistor gates. Each bit of a multiple-bit logical
operation is completely independent and thus can be performed in
parallel incurring no additional performance cost above a single
bit operation.
Comparisons (EQ/NEQ) take O(lg(M)) stages of logic, where M is the
number of bits involved in the comparison. The lg(M) is required
to accumulate the result into a single bit.
Greater than operations, as used to determine whether a hash falls
in a selection range, are a determination of the most significant
not-equivalent bit in the two operands. The operand with that
most-significant-not-equal bit set to be one is greater than the
other. Thus, a greater than operation is also an O(lg(M)) stages
of logic operation. Optimized implementations of arithmetic
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operations are also O(lg(M)) due to propagation of the carry bit.
Setting a counter is simply loading a register with a state. Such
an operation is simple and fast O(1). Incrementing or decrementing
a counter is a read, followed by an arithmetic operation followed
by a store. Making the register dual-ported does take additional
space, but it is a well-understood technique. Thus, the
increment/decrement is also an O(lg(M)) operation.
Hashing functions come in a variety of forms. The computation
involved in a standard Cyclic Redundancy Code (CRC) for example are
essentially a set of XOR operations, where the intermediate result
is stored and XORed with the next chunk of data. There are only
O(1) operations and no log complexity operations. Thus, a simple
hash function, such as CRC or generalizations thereof, can be
implemented in hardware very efficiently.
At the other end of the range of complexity, the MD5 function uses
a large number of bit-wise conditional operations and arithmetic
operations. The former are O(1) operations and the latter are
O(lg(M)). MD5 specifies 256 32b ADD operations per 16B of input
processed. Consider processing 10Gb/sec at 100MHz (this processing
rate appears to be currently available). This requires processing
12.5B/cycle, and hence at least 200 adders, a sizeable
number. Because of data dependencies within the MD5 algorithm, the
adders cannot be simply run in parallel, thus requiring either
faster clock rates and/or more advanced architectures. Thus
selection hashing functions as complex as MD5 may be precluded from
ubiquitous use at full line rate. This motivates exploring the use
of selection hash functions with complexity somewhere between that
of MD5 and CRC. However, identification hashing with MD5 on only
selected packets is feasible at a sufficiently low sampling rate.
10 Applications
We first describe several representative operational applications
that require traffic measurements at various levels of temporal and
spatial granularity enabled by a PSAMP device.
10.1 Baseline Measurement and Drill Down
Packet sampling is ideally suited to determine the composition of
the traffic across a network. The approach is to enable measurement
on a cut-set of the network such that each packet entering the
network is seen at least once, for example, on all ingress and
egress links. Unfiltered sampling with a relatively low rate
establishes baseline measurements of the network traffic. Reports
include packet attributes of common interest: source and
destination address and port numbers, prefix, protocol number, type
of service, etc. Traffic matrices are indicated by reporting source
and destination AS matrices. Absolute traffic volumes are estimated
by renormalizing the sampled traffic volumes through division by
either the target sampling rate, or the attained sampling rate (as
derived by interface packet counters included in the report stream)
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Suppose an operator or a measurement based application detects an
interesting subset of traffic identified by a particular packet
attribute. Real-time drill-down to that subset is achieved by
instantiating a new measurement process at the PSAMP device from
which the subset was reported. The selection process of the new
measurement process filters according to the attribute of interest,
and composes with sampling if necessary to manage the rate of
packet selection.
10.2 Customer Performance
Hash-based sampling enables the tracking of the performance
experience by customer traffic, customers identified by a
list of source or destination prefixes, or by ingress or egress
interfaces. Operational uses include the verification of SLAs, and
troubleshooting following a customer complaint.
In this application, Trajectory Sampling is enabled at all ingress
and egress interfaces. The label hash is used to match up ingress
and egress samples. Rates of loss in transit between ingress and
egress are estimated from the proportion of trajectories for which
no egress report is received. Note loss of customer packets is
distinguishable from loss of packet reports through use of report
sequence numbers. Assuming synchronization of clock between PSAMP
devices, delay of customer traffic across the network may also be
measured.
Extending hash-sampling to all interfaces in the network would
enable attribution of poor performance to individual network links.
10.3 Troubleshooting
PSAMP can also be used to diagnose problems whose occurrence is
evident from aggregate statistics, per interface utilization and
packet loss statistics. These statistics are typically moving
averages over relatively long time windows, e.g., 5 minutes, and
serve as a coarse-grain indication of operational health of the
network. The most common method of obtaining such measurements are
through the appropriate SNMP MIBs (MIB-II and vendor-specific
MIBs.)
Suppose an operator detects a link that is persistently overloaded
and experiences significant packet drop rates. There is a wide
range of potential causes: routing parameters (e.g., OSPF link
weights) that are poorly adapted to the traffic matrix, e.g.,
because of a shift in that matrix; a denial of service attack or a
flash crowd; a routing problem (link flapping). In most cases,
aggregate link statistics are not sufficient to distinguish between
such causes, and to decide on an appropriate corrective action. For
example, if routing over two links is unstable, and the links flap
between being overloaded and inactive, this might be averaged out
in a 5 minute window, indicating moderate loads on both links.
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Baseline PSAMP measurement the congested link, as described in
Section 10.1, enables measurements that are fine grained in both
space and time. The operator has to be able to determine how many
bytes/packets are generated for each source/destination address,
port number, and prefix, or other attributes, such as protocol
number, MPLS forwarding equivalence class (FEC), type of service,
etc. This allows to pinpoint precisely the nature of the offending
traffic. For example, in the case of a DDoS attack, the operator
would see a significant fraction of traffic with an identical
destination address.
In certain circumstances, precise information about the spatial
flow of traffic through the network domain is required to detect
and diagnose problems and verify correct network behavior. In the
case of the overloaded link, it would be very helpful to know the
precise set of paths that packets traversing this link follow. This
would readily reveal a routing problem such as a loop, or a link
with a misconfigured weight. More generally, complex diagnosis
scenarios can benefit from measurement of traffic intensities (and
other attributes) over a set of paths that is constrained in some
way. For example, if a multihomed customer complains about
performance problems on one of the access links from a particular
source address prefix, the operator should be able to examine in
detail the traffic from that source prefix which also traverses the
specified access link towards the customer.
While it is in principle possible to obtain the spatial flow of
traffic through auxiliary network state information, e.g., by
downloading routing and forwarding tables from routers, this
information is often unreliable, outdated, voluminous, and
contingent on a network model. For operational purposes, a direct
observation of traffic flow is more reliable, as it does not depend
on any such auxiliary information. For example, if there was a bug
in a router's software, direct observation would allow to diagnose
the effect of this bug, while an indirect method would not.
Trajectory sampling by enabling common hash-based sampling on all
routers in a domain supports such diagnoses. In particular, routing
loops are revealed as cycles in trajectories.
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11 References
[B88] R.T. Braden, A pseudo-machine for packet monitoring and
statistics, in Proc ACM SIGCOMM 1988
[DuGr01] N. G. Duffield and M. Grossglauser, Trajectory Sampling for
Direct Traffic Observation, IEEE/ACM Trans. on Networking, 9(3), pp.
280-292, June 2001.
[FHK02] S. Floyd, M. Handley. E. Kohler, Problem Statement for
DCCP, Internet Draft draft-ietf-dccp-problem-00.txt, work in
progress, October 2002.
[LCTV02] W.S. Lai, B.Christian, R.W. Tibbs, S. Van den Berghe, A
Framework for Internet Traffic Engineering Measurement, Internet
Draft draft-ietf-tewg-measure-03.txt, work in progress, September
2002.
[PAMM98] V. Paxson, G. Almes, J. Mahdavi, M. Mathis, Framework for
IP Performance Metrics, RFC 2330, May 1998
[QZCZCN02] J. Quittek, T. Zseby, B. Claise, S. Zander, G. Carle,
K.C. Norseth, Requirements for IP Flow Information Export,
Internet Draft draft-ietf-ipfix-reqs-06.txt, work in progress,
October 2002.
[SPSJTKS01] A. C. Snoeren, C. Partridge, L. A. Sanchez, C. E. Jones,
F. Tchakountio, S. T. Kent, W. T. Strayer, Hash-Based IP Traceback,
Proc. ACM SIGCOMM 2001, San Diego, CA, September 2001.
[ZMR02] T. Zseby, M. Molina, F. Raspall, Sampling and Filtering
Techniques for IP Packet Selection, Internet Draft
draft-ietf-psamp-sample-tech-00.txt, work in progress, October
2003.
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12 Authors' Addresses
Nick Duffield
AT&T Labs - Research
Room B-139
180 Park Ave
Florham Park NJ 07932, USA
Phone: +1 973-360-8726
Email: duffield@research.att.com
Albert Greenberg
AT&T Labs - Research
Room A-161
180 Park Ave
Florham Park NJ 07932, USA
Phone: +1 973-360-8730
Email: albert@research.att.com
Matthias Grossglauser
AT&T Labs - Research
Room A-167
180 Park Ave
Florham Park NJ 07932, USA
Phone: +1 973-360-7172
Email: mgross@research.att.com
Jennifer Rexford
AT&T Labs - Research
Room A-169
180 Park Ave
Florham Park NJ 07932, USA
Phone: +1 973-360-8728
Email: jrex@research.att.com
Derek Chiou
Avici Systems
101 Billerica Ave
North Billerica, MA 01862
Phone: +1 978-964-2017
Email: dchiou@avici.com
Peram Marimuthu
Cisco Systems
170, W. Tasman Drive
San Jose, CA 95134
Phone: (408) 527-6314
Email: peram@cisco.com
Ganesh Sadasivan
Cisco Systems
170 W. Tasman Drive
San Jose, CA 95134
Phone: (408) 527-0251
Email: gsadasiv@cisco.com
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13 Intellectual Property Statement
AT&T Corp. may own intellectual property applicable to this
contribution. AT&T is currently reviewing its licensing intent
relative to the Intellectual Property and will notify the IETF when
AT&T has made a determination of that intent.
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