Coordinated sampling sans Origin-Destination identifiers: Algorithms and analysis

Sekar, Vyas; Gupta, Anupam; Reiter, Michael K.; Zhang, Hui

doi:10.1109/comsnets.2010.5432011

Cited by 10 publications

(9 citation statements)

References 47 publications

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“…cSamp [21] coordinates network-wide routers using a hash-based method to sample packets that carry the OD pair information. To make cSamp practical, cSamp-T [20] removes the assumption of OD pair information on packet headers and Decor [23] applies local information to avoid using central controller.…”

Section: Related Workmentioning

confidence: 99%

“…For example, cSamp [21] uses the hash values of the 5-tuples of packets to distribute sampling load among routers. However, cSamp requires all packets to carry their ingress-egress pairs, which are not available in practical networks [20]. The only two approaches that can achieve per-flow monitoring and load distribution are rulebased and aggregation-based flow monitoring.…”

Section: Introductionmentioning

confidence: 97%

“…These tasks usually require the monitoring infrastructure to provide a complete, reliable, and accurate measurement of networkwide flow traffic. Recent studies [21] [20] [23] [30] have addressed two essential requirements of traffic monitoring, load distribution and per-flow monitoring.…”

Section: Introductionmentioning

confidence: 99%

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Distributed and collaborative traffic monitoring in software defined networks

Qian

2014

Proceedings of the Third Workshop on Hot Topics in Software Defined Networking

103

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Network traffic monitoring supports fundamental network management tasks. However, monitoring tasks introduce non-trivial overhead to network devices such as switches. We propose a Distributed and Collaborative Monitoring system, named DCM, with the following properties. First, DCM allows switches to collaboratively achieve flow monitoring tasks and balance measurement load. Second, DCM is able to perform per-flow monitoring, by which different groups of flows are monitored using different actions. Third, DCM is a memory-efficient solution for switch data plane and guarantees system scalability. DCM uses novel two-stage Bloom filters to represent monitoring rules using small memory space. It utilizes the centralized SDN control to install, update, and reconstruct the two-stage Bloom filters in the switch data plane. We study how DCM performs two representative monitoring tasks, namely flow size counting and packet sampling, and evaluate its performance. Experiments using real data center and ISP traffic data on real network topologies show that DCM achieves highest measurement accuracy among existing solutions given the same memory budget of switches.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

See 1 more Smart Citation

Distributed and collaborative traffic monitoring in software defined networks

Qian

2014

Proceedings of the Third Workshop on Hot Topics in Software Defined Networking

103

View full text Add to dashboard Cite

show abstract

“…For example, cSamp [22] uses the hash value of the 5-tuple of a packet to distribute sampling load among routers. However, cSamp requires all packets to carry their ingress-egress pairs, which are not available in practical networks [21]. The only two approaches that can achieve perflow monitoring and load distribution are rule-based and aggregationbased flow monitoring.…”

Section: Introductionmentioning

confidence: 99%

Distributed Collaborative Monitoring in Software Defined Networks

Yu,

Chen,

2014

Preprint

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We propose a Distributed and Collaborative Monitoring system, DCM, with the following properties. First, DCM allows switches to collaboratively achieve flow monitoring tasks and balance measurement load. Second, DCM is able to perform per-flow monitoring, by which different groups of flows are monitored using different actions. Third, DCM is a memory-efficient solution for switch data plane and guarantees system scalability. DCM uses a novel two-stage Bloom filters to represent monitoring rules using small memory space. It utilizes the centralized SDN control to install, update, and reconstruct the two-stage Bloom filters in the switch data plane. We study how DCM performs two representative monitoring tasks, namely flow size counting and packet sampling, and evaluate its performance. Experiments using real data center and ISP traffic data on real network topologies show that DCM achieves highest measurement accuracy among existing solutions given the same memory budget of switches.

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“…This formulation assumes that routers in the middle of the network can infer the OD-pair from packet headers using MPLS labels or ingress-egress prefix maps[6]. cSamp can also be implemented without OD-pair identifiers[40]. For clarity, we describe the simpler approach using OD-pairs 6.…”

mentioning

confidence: 99%

Revisiting the case for a minimalist approach for network flow monitoring

Sekar

Reiter

Zhang

2010

Proceedings of the 10th ACM SIGCOMM Conference on Internet Measurement

Self Cite

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Network management applications require accurate estimates of a wide range of flow-level traffic metrics. Given the inadequacy of current packet-sampling-based solutions, several application-specific monitoring algorithms have emerged. While these provide better accuracy for the specific applications they target, they increase router complexity and require vendors to commit to hardware primitives without knowing how useful they will be to meet the needs of future applications.In this paper, we show using trace-driven evaluations that such complexity and early commitment may not be necessary. We revisit the case for a "minimalist" approach in which a small number of simple yet generic router primitives collect flow-level data from which different traffic metrics can be estimated. We demonstrate the feasibility and promise of such a minimalist approach using flow sampling and sample-and-hold as sampling primitives and configuring these in a network-wide coordinated fashion using cSamp. We show that this proposal yields better accuracy across a collection of application-level metrics than dividing the same memory resources across metric-specific algorithms. Moreover, because a minimalist approach enables late binding to what applicationlevel metrics are important, it better insulates router implementations and deployments from changing monitoring needs.

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Coordinated sampling sans Origin-Destination identifiers: Algorithms and analysis

Cited by 10 publications

References 47 publications

Distributed and collaborative traffic monitoring in software defined networks

Distributed and collaborative traffic monitoring in software defined networks

Distributed Collaborative Monitoring in Software Defined Networks

Revisiting the case for a minimalist approach for network flow monitoring

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