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Monarch Butterfly Optimization for Reliable Scheduling in Cloud

Computers, Materials & Continua 2021年第12期69卷 3693-3710页

作者： B.Gomathi S.T.Suganthi Karthikeyan Krishnasamy J.Bhuvana Department of Information Technology Hindusthan College of Engineering and TechnologyCoimbatore641032India Department of Computer Networking Lebanese French UniversityErbil44001Iraq Department of Information Technology Coimbatore Institute of TechnologyCoimbatore641014India Department of MCA School of Computer Science and ITJain(Deemed to be)UniversityBangalore560069India

Enterprises have extensively taken on cloud computing environment since it provides on-demand virtualized cloud application *** scheduling of the cloud tasks is a well-recognized NP-hard *** Task scheduling problem is convoluted while convincing different objectives,which are dispute in *** this paper,Multi-Objective Improved Monarch Butterfly Optimization(MOIMBO)algorithm is applied to solve multi-objective task scheduling problems in the cloud in preparation for Pareto optimal *** different dispute objectives,such as makespan,reliability,and resource utilization,are deliberated for task scheduling *** Epsilonfuzzy dominance sort method is utilized in the multi-objective domain to elect the foremost solutions from the Pareto optimal solution ***,together with the Self Adaptive and Greedy Strategies,have been incorporated to enrich the performance of the proposed *** capability and effectiveness of the proposed algorithm are measured with NSGA-II and MOPSO *** simulation results prompt that the proposed MOIMBO algorithm extensively diminishes the makespan,maximize the reliability,and guarantees the appropriate resource utilization when associating it with identified existing algorithms.

关键词： Improved monarch butterfly optimization cloud computing makespan reliability fuzzy dominance task scheduling

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