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

被引:7
|
作者
Xing, Huanlai [1 ,2 ]
Qu, Rong [1 ]
Kendall, Graham [1 ,4 ]
Bai, Ruibin [3 ]
机构
[1] Univ Nottingham, Nottingham NG8 1BB, Notts, England
[2] Southwest Jiaotong Univ, Chengdu, Peoples R China
[3] Univ Nottingham Ningbo, Ningbo, Zhejiang, Peoples R China
[4] Univ Nottingham, Kuala Lumpur, Malaysia
基金
英国工程与自然科学研究理事会; 中国国家自然科学基金;
关键词
evolutionary computation; multicast routing; network coding; GENETIC ALGORITHM; MULTICAST;
D O I
10.1057/jors.2013.79
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
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.
引用
收藏
页码:1261 / 1277
页数:17
相关论文
共 50 条
  • [11] Dynamic inter-SLA resource sharing in path-oriented differentiated services networks
    Cheng, Yu
    Zhuang, Weihua
    IEEE-ACM TRANSACTIONS ON NETWORKING, 2006, 14 (03) : 657 - 670
  • [12] Resource minimization in network coding by integer programming
    Department of Industrial and Information Systems Engineering, Soongsil University, 369 Sangdo-Ro, Dongjak-Gu, Seoul, Korea, Republic of
    ICIC Express Lett Part B Appl., 3 (785-789):
  • [13] Genetic Algorithm and its Application in the path-oriented test data automatic generation
    Liu Shimin
    Wang Zhangang
    CEIS 2011, 2011, 15
  • [14] EFFICIENT PATH-ORIENTED TEST DATA GENERATION ALGORITHM FOR EFSM WITH SIMULATED ANNEALING
    Cheng, Xichao
    Cheng, Yong
    Zhao, Ruilian
    THIRD INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND TECHNOLOGY (ICCET 2011), 2011, : 665 - 670
  • [15] Genetic representations for evolutionary minimization of network coding resources
    Kim, Minkyu
    Aggarwa, Varun
    O'Reilly, Una-May
    Medard, Muriel
    Kim, Wonsik
    APPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS, 2007, 4448 : 21 - +
  • [16] Automatic Path-oriented Test Data Generation Using a Multi-population Genetic Algorithm
    Chen, Yong
    Zhong, Yong
    ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 1, PROCEEDINGS, 2008, : 566 - 570
  • [17] An Modified PBIL for Network Coding Resource Minimization in Dynamic Network Environment
    Xing, Huanlai
    Song, Fuhong
    Wang, Zhaoyuan
    Li, Tianrui
    Yang, Yan
    2016 2ND IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATIONS (ICCC), 2016, : 1133 - 1137
  • [18] The Research of path-oriented test data generation based on a mixed ant colony system algorithm and genetic algorithm
    Yi, Minjie
    2012 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING (WICOM), 2012,
  • [19] An improved quantum-inspired evolutionary algorithm for coding resource optimization based network coding multicast scheme
    Xing, Huanlai
    Ji, Yuefeng
    Bai, Lin
    Sun, Yongmei
    AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS, 2010, 64 (12) : 1105 - 1113
  • [20] A Path-Oriented Test Data Generation Approach Hybridizing Genetic Algorithm and Artificial Immune System
    Bhattacharjee, Gargi
    Saluja, Ashish Singh
    COMPUTATIONAL INTELLIGENCE IN DATA MINING, 2019, 711 : 649 - 658