Cross-layer optimizations for intersession network coding on practical 2-hop relay networks

Chih Chun Wang, Abdallah Khreishah, Ness B. Shroff

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

20 Scopus citations

Abstract

Full characterization of Intersession Network Coding (INC), i.e., coding across multiple unicast sessions, is notoriously challenging. Nonetheless, the problem can be made tractable when considering practical constraints that restrict the types of INC schemes of interest. This paper characterizes the INC capacity of 2-session wireless 2-hop relay networks with a packet erasure channel model and a round-based feedback schedule motivated by the usage of "reception reports" in practical protocols such as COPE. The capacity regions are formulated as linear programming problems, which admit simple concatenation with other competing techniques such as opportunistic routing (OpR), and cross-layer (CL) optimization. Extensive numerical evaluation is conducted on 1000 random topologies, which compares and quantifies the throughput benefits of INC, OpR, and CL, and their arbitrary combinations. The results show that by combining all three techniques of INC, OpR, and CL, the throughput of a wireless 2-hop relay network can be improved by 100-500% over the benchmark single-path routing solution depending on the number of sessions to be coded together

Original languageEnglish (US)
Title of host publicationConference Record - 43rd Asilomar Conference on Signals, Systems and Computers
Pages771-775
Number of pages5
DOIs
StatePublished - 2009
Externally publishedYes
Event43rd Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: Nov 1 2009Nov 4 2009

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other43rd Asilomar Conference on Signals, Systems and Computers
Country/TerritoryUnited States
CityPacific Grove, CA
Period11/1/0911/4/09

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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