Computer Science

Computer Science ›› 2020, Vol. 47 ›› Issue (6): 236-241.doi: 10.11896/jsjkx.191000139

Special Issue: Network and communication

• Computer Network • Previous Articles     Next Articles

Hybrid Software Defined Network Energy Efficient Routing Algorithm Based on Genetic Algorithm

ZHANG Ju1,2, WANG Hao1, LUO Shu-ting1, GENG Hai-jun1,2, YIN Xia3   

  1. 1 School of Software Engineering,Shanxi University,Taiyuan 030006,China
    2 State Key Laboratory of Networking and Switching Technology (Beijing University of Posts and Telecommunications),Beijing 100876,China
    3 Department of Computer Science and Technology,Tsinghua University,Beijing 100084,China
  • Received:2019-10-22 Online:2020-06-15 Published:2020-06-10
  • About author:ZHANG Ju,born in 1972,master,lecture.His main research interests include routing protocols and network security.
    GENG Hai-jun,born in 1983,Ph.D.His main research interests include future Internet architecture and largescale Internet routing.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (61702315),Open Foundation of State Key Laboratory of Networking and Switching Technoogy (Beijing University of Posts and Telecommunications) (SKLNST-2018-19) and National Key Research and Deve-lopment Program of China (2018YFB1800401).

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Abstract: With the rapid development of software defined network (SDN) technology,the Internet will be in the hybrid SDN network where the traditional network devices and SDN devices coexist for a long time.It is a key scientific problem to studyenergy efficient algorithm in hybrid SDN networks.Therefore,this paper proposes a hybrid software defined network energy efficient routing algorithm based on genetic algorithm (EEHSDNGA).This paper is devoted to solving two problems.Firstly,how to choose some traditional network devices to upgrade to SDN devices in network.Secondly,how to shut down links.This paper employs genetic algorithm to solve the first problem.To solve the second problem,this paper proposes a link criticality model,which closes the links in the network one by one according to the importance of the links.The experimental results show that the energy saving ratio of EEHSDNGA in Abilene network is 36%,and in GEANT network is 42.5%.The energy saving ratio of EEHSDNGA is better than that of LF,HEATE and EEGAH.

Key words: Deployment overhead ratio, Genetic algorithm, Hybrid software defined network, Link criticality model

CLC Number: 

  • TP393
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