A path-oriented encoding evolutionary algorithm for network coding resource minimization

Huanlai Xing, Rong Qu, Graham Kendall, Ruibin Bai

Research output: Journal PublicationArticlepeer-review

6 Citations (Scopus)
1 Downloads (Pure)

Abstract

Network coding is an emerging telecommunication technique, where any intermediate node is allowed to recombine incoming data if necessary. This technique helps to increase the throughput, however, very likely at the cost of huge amount of computational overhead, due to the packet recombination performed (ie coding operations). Hence, it is of practical importance to reduce coding operations while retaining the benefits that network coding brings to us. In this paper, we propose a novel evolutionary algorithm (EA) to minimize the amount of coding operations involved. Different from the state-of-the-art EAs which all use binary encodings for the problem, our EA is based on path-oriented encoding. In this new encoding scheme, each chromosome is represented by a union of paths originating from the source and terminating at one of the receivers. Employing path-oriented encoding leads to a search space where all solutions are feasible, which fundamentally facilitates more efficient search of EAs. Based on the new encoding, we develop three basic operators, that is, initialization, crossover and mutation. In addition, we design a local search operator to improve the solution quality and hence the performance of our EA. The simulation results demonstrate that our EA significantly outperforms the state-of-the-art algorithms in terms of global exploration and computational time.

Original languageEnglish
Pages (from-to)1261-1277
Number of pages17
JournalJournal of the Operational Research Society
Volume65
Issue number8
DOIs
Publication statusPublished - Aug 2014

Keywords

  • evolutionary computation
  • multicast routing
  • network coding

ASJC Scopus subject areas

  • Management Information Systems
  • Strategy and Management
  • Management Science and Operations Research
  • Marketing

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