Blockchain-Assisted Server Placement With Elitist Preserved Genetic Algorithm in Edge Computing

被引:7
|
作者
Li, Zheng [1 ,2 ]
Li, Guosheng [3 ]
Bilal, Muhammad [4 ]
Liu, Dongqing [5 ]
Huang, Tao [6 ]
Xu, Xiaolong [1 ,2 ]
机构
[1] Guizhou Univ, State Key Lab Publ Big Data, Guiyang 550025, Guizhou, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Nanjing 210023, Peoples R China
[3] Weifang Univ Sci & Technol, Shandong Prov Univ Lab Protected Hort, Weifang 262700, Peoples R China
[4] Hankuk Univ Foreign Studies, Dept Comp & Elect Syst Engn, Yongin 17035, South Korea
[5] Nanjing Meteorol Bur, Nanjing 210009, Peoples R China
[6] Silicon Lake Coll, Sch Comp Sci & Technol, Suzhou 215332, Peoples R China
关键词
Blockchain; edge computing (EC); server placement; SECURITY; CLOUD;
D O I
10.1109/JIOT.2023.3290568
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The distribution of edge resources in the edge computing (EC) environment has an important impact on the Quality of Service (QoS) of edge services. Unreasonable server placement will inevitably lead to problems, such as server overload or underload, deteriorating workload balancing and service wait time. Therefore, the key issue to be addressed in server placement is how to enhance the QoS of edge services through efficient edge server (ES) placement strategies under multiple requirements, such as average task wait time and data privacy. EC-assisted with blockchain technology was argued to be the most potential solution. In this article, we propose a blockchain-assisted secure ES placement algorithm named ETS_GA. ETS_GA is based on the elite-preserving genetic algorithm (EGA), which is proven to converge. The premature problem of traditional genetic algorithm (GA) is effectively solved by using tabu search (TS) and niche sharing (NS). In addition, we construct an adaptive state supervising machine (ASM) to realize real-time algorithm supervision and adaptively iterate the optimization strategy. Blockchain-based privacy protection methods are also deployed in the placed servers to provide real-time privacy protection. Finally, our proposed method is experimentally compared with four baselines using the real Shanghai Telecom base station data set, whose results demonstrate the superiority of ETS_GA in terms of convergence and global search capability.
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页码:21401 / 21409
页数:9
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