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On minimizing coding operations in network coding based multicast: an evolutionary algorithm

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Abstract

In telecommunications networks, to enable a valid data transmission based on network coding, any intermediate node within a given network is allowed, if necessary, to perform coding operations. The more coding operations needed, the more coding resources consumed and thus the more computational overhead and transmission delay incurred. This paper investigates an efficient evolutionary algorithm to minimize the amount of coding operations required in network coding based multicast. Based on genetic algorithms, we adapt two extensions in the proposed evolutionary algorithm, namely a new crossover operator and a neighbourhood search operator, to effectively solve the highly complex problem being concerned. The new crossover is based on logic OR operations to each pair of selected parent individuals, and the resulting offspring are more likely to become feasible. The aim of this operator is to intensify the search in regions with plenty of feasible individuals. The neighbourhood search consists of two moves which are based on greedy link removal and path reconstruction, respectively. Due to the specific problem feature, it is possible that each feasible individual corresponds to a number of, rather than a single, valid network coding based routing subgraphs. The neighbourhood search is applied to each feasible individual to find a better routing subgraph that consumes less coding resource. This operator not only improves solution quality but also accelerates the convergence. Experiments have been carried out on a number of fixed and randomly generated benchmark networks. The results demonstrate that with the two extensions, our evolutionary algorithm is effective and outperforms a number of state-of-the-art algorithms in terms of the ability of finding optimal solutions.

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Acknowledgments

This work was supported by NSFC (No. 6117 1103, No.61372118), Doctoral Fund of MOE (No.20120005130001), Natural Science Foundation of Zhejiang Province (No. LQ13F 030011), the Fundamental Research Funds for the Central Universities (2682014RC23), the China Scholarship Council (CSC), P.R.China, and University of Nottingham, UK.

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Authors and Affiliations

  1. School of Information Science and Technology, Southwest Jiaotong University, 111, North 1st Section, 2nd Ring Rd, Chengdu, 610031, People’s Republic of China

    Huanlai Xing

  2. ASAP Group, School of Computer Science, University of Nottingham, Nottingham, NG8 1BB, United Kingdom

    Rong Qu

  3. State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, 10 XITUCHENG Rd, Haidian District, Beijing, 100876, People’s Republic of China

    Lin Bai & Yuefeng Ji

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  1. Huanlai Xing
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  2. Rong Qu
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Correspondence to Huanlai Xing.

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Xing, H., Qu, R., Bai, L. et al. On minimizing coding operations in network coding based multicast: an evolutionary algorithm. Appl Intell 41, 820–836 (2014). https://doi.org/10.1007/s10489-014-0559-4

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