Network tomography from aggregate loss reports

Duffield, Nick; Arya, Vijay; Bellino, Rémy; Friedman, Timur; Horowitz, J.; Towsley, Don; Turletti, Thierry

doi:10.1016/j.peva.2005.07.022

Cited by 8 publications

(4 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The inference methods developed in this paper build on and extend those in the MINC project; see [5], [9] and related unicast approaches [10], [11]. A brief introduction to MINC is given in Section I; part of our work focuses on how to apply MINC techniques on measuring one way performance from a measurement host to an edge router.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

GRE Encapsulated Multicast Probing: A Scalable Technique for Measuring One-Way Loss

Gu¹,

Breslau²,

Duffield³

et al. 2008

2008 Proceedings IEEE INFOCOM - The 27th Conference on Computer Communications

View full text Add to dashboard Cite

Internet service providers increasingly wish to monitor the performance of customer traffic within their networks. This paper addresses the problem of scalably performing one-way loss measurements across specific network paths. Our solution addresses the issue of scale by exploiting measurement features of the deployed network infrastructure to a large degree. There are three components. Firstly, GRE tunneling is used to control the path followed by measurement traffic in the network. Secondly, innovative probing methods, coupled with standard measurement capabilities, such as NetFlow, are used to isolate the performance of groups of measurement packets. Thirdly, we exploit and extend tomographic inference methods in order to extract the performance of probe traffic on customer paths within the network. This combination yields a powerful yet lightweight method to determine customer performance within the network.

show abstract

Section: Related Workmentioning

confidence: 99%

“…(A threshold ε = 10 −4 was used). In [9] a moment estimator was derived for α based on the same aggregate measurements. Although moment estimator can be computed explicitly, the terminal EM iterator was found numerically to be noticeably more accurate in test cases.…”

Section: E Em Algorithm For Aggregate Mlementioning

confidence: 99%

GRE Encapsulated Multicast Probing: A Scalable Technique for Measuring One-Way Loss

Gu¹,

Breslau²,

Duffield³

et al. 2008

2008 Proceedings IEEE INFOCOM - The 27th Conference on Computer Communications

View full text Add to dashboard Cite

show abstract

“…In this configuration, the ability to distinguish individual packets is limited by the router level measurement at R2, which is assumed to report only aggregates. Therefore we must use the aggregate MINC estimator [4] on packet aggregates reported by R2. Configuration C: Observation at a Measurement Host and Reflection.…”

Section: Configuration A: Probe Collection At Two Measurement Hostsmentioning

confidence: 99%

GRE encapsulated multicast probing

Gu¹,

Breslau

Duffield

et al. 2007

Proceedings of the 2007 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems

View full text Add to dashboard Cite

show abstract

“…A body of work on Multicast Inference of Network Characteristics (MINC) has shown how to infer average packet loss rates [3,4] and delay distributions [5] of network links, and even the network topology itself [6]. More recently [7], tunneling has been used to create a multicast measurement overlay with physical network edge points acting as branch points and this new measurement technology has also rekindled interest in using tomographic methods.…”

Section: Introductionmentioning

confidence: 99%