Modified firefly algorithm for workflow scheduling in cloud-edge environment

被引:62
作者
Bacanin, Nebojsa [1 ]
Zivkovic, Miodrag [1 ]
Bezdan, Timea [1 ]
Venkatachalam, K. [2 ]
Abouhawwash, Mohamed [3 ,4 ]
机构
[1] Singidunum Univ, Danijelova 32, Belgrade 11000, Serbia
[2] Univ Hradec Kralove, Fac Sci, Dept Appl Cybernet, Hradec Kralove 50003, Czech Republic
[3] Mansoura Univ, Fac Sci, Dept Math, Mansoura 35516, Egypt
[4] Michigan State Univ, Dept Computat Math Sci & Engn CMSE, E Lansing, MI 48824 USA
关键词
Edge computing; Swarm intelligence; Workflow scheduling; Firefly algorithm; Genetic operator; Quasi-reflection-based learning; PARTICLE SWARM OPTIMIZATION;
D O I
10.1007/s00521-022-06925-y
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Edge computing is a novel technology, which is closely related to the concept of Internet of Things. This technology brings computing resources closer to the location where they are consumed by end-users-to the edge of the cloud. In this way, response time is shortened and lower network bandwidth is utilized. Workflow scheduling must be addressed to accomplish these goals. In this paper, we propose an enhanced firefly algorithm adapted for tackling workflow scheduling challenges in a cloud-edge environment. Our proposed approach overcomes observed deficiencies of original firefly metaheuristics by incorporating genetic operators and quasi-reflection-based learning procedure. First, we have validated the proposed improved algorithm on 10 modern standard benchmark instances and compared its performance with original and other improved state-of-the-art metaheuristics. Secondly, we have performed simulations for a workflow scheduling problem with two objectives-cost and makespan. We performed comparative analysis with other state-of-the-art approaches that were tested under the same experimental conditions. Algorithm proposed in this paper exhibits significant enhancements over the original firefly algorithm and other outstanding metaheuristics in terms of convergence speed and results' quality. Based on the output of conducted simulations, the proposed improved firefly algorithm obtains prominent results and managed to establish improvement in solving workflow scheduling in cloud-edge by reducing makespan and cost compared to other approaches.
引用
收藏
页码:9043 / 9068
页数:26
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