Arbitrarily varying networks: Capacity-achieving computationally efficient codes

Peida Tian, Sidharth Jaggi, Mayank Bakshi, Oliver Kosut

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

1 Citation (Scopus)

Abstract

We consider the problem of communication over a network containing a hidden and malicious adversary that can control a subset of network resources, and aims to disrupt communications. We focus on omniscient node-based adversary, i.e., the adversary can control a subset of nodes, and knows the message, network code and packets on all links. Characterizing information-theoretically optimal communication rates as a function of network parameters and bounds on the adversarially controlled network is in general open, even for unicast (single source, single destination) problems. In this work we characterize the information-theoretically optimal randomized capacity of such problems, i.e., under the assumption that the source node shares (an asymptotically negligible amount of) independent common randomness with each network node a priori. We propose a novel computationally-efficient communication scheme whose rate matches a natural information-theoretically 'erasure outer bound' on the optimal rate. Our schemes require no prior knowledge of network topology, and can be implemented in a distributed manner as an overlay on top of classical distributed linear network coding.

Original languageEnglish (US)
Title of host publicationProceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2139-2143
Number of pages5
Volume2016-August
ISBN (Electronic)9781509018062
DOIs
StatePublished - Aug 10 2016
Event2016 IEEE International Symposium on Information Theory, ISIT 2016 - Barcelona, Spain
Duration: Jul 10 2016Jul 15 2016

Other

Other2016 IEEE International Symposium on Information Theory, ISIT 2016
CountrySpain
CityBarcelona
Period7/10/167/15/16

Fingerprint

Communication
Vertex of a graph
Linear networks
Network coding
Subset
Optimal Rates
Network Coding
Topology
Overlay
Prior Knowledge
Network Topology
Randomness
Resources

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

Cite this

Tian, P., Jaggi, S., Bakshi, M., & Kosut, O. (2016). Arbitrarily varying networks: Capacity-achieving computationally efficient codes. In Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory (Vol. 2016-August, pp. 2139-2143). [7541677] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT.2016.7541677

Arbitrarily varying networks : Capacity-achieving computationally efficient codes. / Tian, Peida; Jaggi, Sidharth; Bakshi, Mayank; Kosut, Oliver.

Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory. Vol. 2016-August Institute of Electrical and Electronics Engineers Inc., 2016. p. 2139-2143 7541677.

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

Tian, P, Jaggi, S, Bakshi, M & Kosut, O 2016, Arbitrarily varying networks: Capacity-achieving computationally efficient codes. in Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory. vol. 2016-August, 7541677, Institute of Electrical and Electronics Engineers Inc., pp. 2139-2143, 2016 IEEE International Symposium on Information Theory, ISIT 2016, Barcelona, Spain, 7/10/16. https://doi.org/10.1109/ISIT.2016.7541677
Tian P, Jaggi S, Bakshi M, Kosut O. Arbitrarily varying networks: Capacity-achieving computationally efficient codes. In Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory. Vol. 2016-August. Institute of Electrical and Electronics Engineers Inc. 2016. p. 2139-2143. 7541677 https://doi.org/10.1109/ISIT.2016.7541677
Tian, Peida ; Jaggi, Sidharth ; Bakshi, Mayank ; Kosut, Oliver. / Arbitrarily varying networks : Capacity-achieving computationally efficient codes. Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory. Vol. 2016-August Institute of Electrical and Electronics Engineers Inc., 2016. pp. 2139-2143
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