Journal on Communications ›› 2020, Vol. 41 ›› Issue (10): 37-47.doi: 10.11959/j.issn.1000-436x.2020210

Special Issue: 边缘计算

• Topics: Convergence of Communications and Computing for the IoE • Previous Articles     Next Articles

Service function chain embedding algorithm with wireless multicast in mobile edge computing network

Kan WANG1,Nan ZHAO2(),Junhuai LI1,Huaijun WANG1   

  1. 1 School of Computer and Science Engineering,Xi’an University of Technology,Xi’an 710048,China
    2 School of Information and Communication Engineering,Dalian University of Technology,Dalian 116024,China
  • Revised:2020-09-24 Online:2020-10-25 Published:2020-11-05
  • Supported by:
    The National Key Research and Development Program of China(2018YFB1703000);The National Natural Science Foundation of China(61801379);The National Natural Science Foundation of China(61871065);The National Natural Science Foundation of China(61971347);The Open Research Fund from State Key Laboratory of Integrated Services Networks,Xidian University(ISN21-08)

Abstract:

To resolve the excessive system overhead and serious traffic congestion in user-oriented service function chain (SFC) embedding in mobile edge computing (MEC) networks,a content-oriented joint wireless multicast and SFC embedding algorithm was proposed for the multi-base station and multi-user edge networks with MEC servers.By involving four kinds of system overhead,including service flow,server function sustaining power,server function service power and wireless transmission power,an optimization model was proposed to jointly design SFC embedding with multicast beamforming.Firstly,with Lagrangian dual decomposition,the problem was decoupled into two independent subproblems,namely,SFC embedding and multicast beamforming.Secondly,with the L<sub>p</sub> norm penalty term-based successive convex approximation algorithm,the integer programming-based SFC embedding problem was relaxed to an equivalent linear programming one.Finally,the non-convex beamforming optimization problem was transformed into a series of convex ones via the path following technique.Simulation results revealed that the proposed algorithm has good convergence,and is superior to both the optimal SFC embedding with unicasting and random SFC embedding with multicasting in terms of system overhead.

Key words: mobile edge computing, service function chain, multicast beamforming, network function virtualization

CLC Number: 

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