Trajectory sampling for direct traffic observation

By Nick G. Duffield, Matthias Grossglauser. TNET, 2001

430 citations recorded by the source corpus.

Traffic measurement is a critical component for the control and engine ering of communication networks. We argue that traffic measurement should make it possible to obtain the spatial flow of traffic through the domain, i.e., the paths followed by packets between any ingress and egress point of the domain. Most resource allocation and capacity planning tasks can benefit from such information. Also, traffic measurements should be obtained without a routing model and without knowledge of network state. This allows the traffic measurement process to be resilient to network failures and state uncertainty. We propose a method that allows the direct inference of traffic flows through a domain by observing the trajectories of a subset of all packets traversing the network. The key advantages of the method are that 1) it does not rely on routing state; 2) its implementation cost is small; and 3) the measurement reporting traffic is modest and can be controlled precisely. The key idea of the method is to sample packets based on a hash function computed over the packet content. Using the same hash function will yield the same sample set of packets in the entire domain, and enables us to reconstruct packet trajectories.

Subfields: Artificial Intelligence, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/06ff081f78263a253cca74d31e45e706ce0d0de0

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Citations in the corpus

Automated Worm Fingerprinting (2004, methodology): “both use hashing to match packet observations across a network [38, 7], and both Spring et al.”
Data streams: algorithms and applications (2005, background): “High energy particle physics experiments at Fermilab and CERN [120] will so on produce40TBytes/s which will be reduced by real time hardware into800Gb/s data stream: is it careful sampling or carefree sheddin g? Statisticians have the sampling theory: it is now getting applied to IP netw ork streams”
Traffic engineering with traditional IP routing protocols (2002, background): “Fourth, new techniques for packet sampling offer the possibility of direct observation of the offered traffic as it flows through the network [13].”
Continuous queries over data streams (2001, methodology): “Consider the domain of network traffic management for a large network, e.g., the backbone network of an Internet Service Provider (ISP) [ DG00 ].”
Single-packet IP traceback (2002, background): “Duffield and Grossglauser encountered similar requirem ents while sampling a subset of forwarded packets in an attempt to measure traffic flows [17].”
Packet-Level Telemetry in Large Datacenter Networks (2015, background): “Another work [8] proposes sampling packets with a consistent hash function.”
New directions in traffic measurement and accounting (2001, background): “[5] describes a mechanism for identifying packet trajectories in the backbone, not identifying the networks generating the traÆc.”
Hash-based IP traceback (2001, background): “section 5.3). Duffield and Grossglauser encountered similar requirements while sampling a subset of forwarded packets in an attempt to measure traffic flows [ 7 ].”
Making intra-domain routing robust to changing and uncertain traffic demands: understanding fundamental tradeoffs (2003, background): “…engineering tools Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for pro.t or commercial advantage and that copies bear this notice and the full citation on the .rst page.”