A fuzzy logic‐based method for solving the scheduling problem in the cloud environments using a non‐dominated sorted algorithm. (11th February 2019)

• Record Type: Journal Article
• Authors: Wakil, Karzan; Badfar, Arshad; Dehghani, Pooyan; Shoja Sadati, Seyed Mojtaba; Jafari Navimipour, Nima
• Is Part Of: Concurrency and computation. Volume 31:Number 17(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-02-11
• Subjects: cloud computing -- multi‐objective optimization -- particle swarm optimization algorithm -- task scheduling; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.5185
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: Cloud computing as a new model of delivering IT services on the Internet has attained high attention recently. In this new paradigm, efficient service management causes the high quality of provided services. Scheduling as one of the most important duties of service management is a key problem in cloud computing that affects the total system performance. In most cases, the meta‐heuristic methods are used for optimizing the scheduling issues instead of traditional methods. One of the influential evolutionary algorithms for optimizing the complicated problems is a non‐dominated sorting particle swarm optimization (NSPSO) technique. In this paper, we propose a meta‐heuristic technique using the NSPSO model for decreasing total cost and consumed total time. Furthermore, fuzzy set theory is applied to select the best solution. Simulation results have indicated that the efficiency of NSPSO is improved. In the many types of experiment, the proposed NSPSO algorithm was appropriate to keep a good spread of solutions and good converge. In addition, the diversity preserving mechanism applied in NSPSO has improvement against the other two investigated algorithms.