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A fuzzy logic‐based method for solving the scheduling problem in the cloud environments using a non‐dominated sorted algorithm
Author(s) -
Wakil Karzan,
Badfar Arshad,
Dehghani Pooyan,
Shoja Sadati Seyed Mojtaba,
Jafari Navimipour Nima
Publication year - 2019
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5185
Subject(s) - cloud computing , computer science , particle swarm optimization , scheduling (production processes) , sorting , fuzzy logic , meta heuristic , mathematical optimization , distributed computing , cloud service provider , quality of service , algorithm , artificial intelligence , mathematics , cloud computing security , computer network , operating system
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.