ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2021, Vol. 58 ›› Issue (9): 2025-2039.doi: 10.7544/issn1000-1239.2021.20200338

Previous Articles     Next Articles

A Computation Offloading Algorithm with Path Selection Based on K-shell Influence Maximization

Yue Guangxue1,3, Chen Guanglu1,2,3, Lu Min3, Yang Xiaohui1,3, Liu Jianhua1, Huang Chunlan1,3, Yang Zhongming1,3   

  1. 1(College of Information Science and Engineering, Jiaxing University, Jiaxing, Zhejiang 314001);2(State Grid Jibei Dacheng Power Supply Co ., Ltd, Langfang, Hebei 065000);3(College of Science, Jiangxi University of Science and Technology, Ganzhou, Jiangxi 341000)
  • Online:2021-09-01
  • Supported by: 
    This work was supported by the National Natural Science Foundation of China (U19B2015) and the Top-level Talent Project of Zhejiang Province.

Abstract: As edge computing and cloud computing develop in a rapid speed and integrate with each other, resources and services gradually offload from the core network to the edge of the network. Efficient computation offloading algorithm is one of the most important problems in mobile edge computing networks. In order to improve the performance of the algorithm, a computation offloading algorithm with path selection based on K-shell influence maximization is proposed. The K-shell method is used to grade the edge servers by applying the convertibility and maximizing influence model of similar problems. Otherwise, considering the problem of excessive load of edge servers, path overlap (PO) algorithm is constructed, and indicators such as the communication quality, interaction strength, and queue processing ability, etc. are introduced to optimize the performance of the algorithm. The offloading path problem of the optimization calculation task is transformed into the social network impact maximization problem. Based on the idea of maximizing K-shell influence, greedy and heuristic algorithms are optimized and improved, and the K-shell influence maximization computation offloading (Ks-IMCO) algorithm is proposed to solve the problem of computational offloading. Through the comparative analysis of Ks-IMCO and random allocation (RA), path selection with handovers (PSwH) algorithm experiments, the energy consumption and delay of Ks-IMCO algorithm have been significantly improved, which can effectively improve the efficiency of edge computing network computing offloading.

Key words: mobile edge computing, computation offloading, influence maximization, path selection, K-shell

CLC Number: