Robust network tomography in the presence of failures

S. Tati, S. Silvestri, T. He, T. La Porta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Scopus citations

Abstract

In this paper, we study the problem of selecting paths to improve the performance of network tomography applications in the presence of network element failures. We model the robustness of paths in network tomography by a metric called expected rank. We formulate an optimization problem to cover two complementary performance metrics: robustness and probing cost. The problem aims at maximizing the expected rank under a budget constraint on the probing cost. We prove that the problem is NP-Hard. Under the assumption that the failure distribution is known, we propose an algorithm called RoMe with guaranteed approximation ratio. Moreover, since evaluating the expected rank is generally hard, we provide a bound which can be evaluated efficiently. We also consider the case in which the failure distribution is not known, and propose a reinforcement learning algorithm to solve our optimization problem, using RoMe as a subroutine. We run a wide range of simulations under realistic network topologies and link failure models to evaluate our solution against a state-of-the-art path selection algorithm. Results show that our approaches provide significant improvements in the performance of network tomography applications under failures.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Distributed Computing Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages481-492
Number of pages12
ISBN (Electronic)9781479951680
DOIs
StatePublished - Aug 29 2014
Event2014 IEEE 34th International Conference on Distributed Computing Systems, ICDCS 2014 - Madrid, Spain
Duration: Jun 30 2014Jul 3 2014

Publication series

NameProceedings - International Conference on Distributed Computing Systems

Other

Other2014 IEEE 34th International Conference on Distributed Computing Systems, ICDCS 2014
CountrySpain
CityMadrid
Period6/30/147/3/14

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'Robust network tomography in the presence of failures'. Together they form a unique fingerprint.

Cite this