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An efficient cloudlet scheduling via bin packing in cloud computing

Amine Chraibi, Said Ben Alla, Abdellah Ezzati

2022International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering12 citationsDOIOpen Access PDF

Abstract

<p>In this ever-developing technological world, one way to manage and deliver services is through cloud computing, a massive web of heterogenous autonomous systems that comprise adaptable computational design. Cloud computing can be improved through task scheduling, albeit it being the most challenging aspect to be improved. Better task scheduling can improve response time, reduce power consumption and processing time, enhance makespan and throughput, and increase profit by reducing operating costs and raising the system reliability. This study aims to improve job scheduling by transferring the job scheduling problem into a bin packing problem. Three modifies implementations of bin packing algorithms were proposed to be used for task scheduling (MBPTS) based on the minimisation of makespan. The results, which were based on the open-source simulator CloudSim, demonstrated that the proposed MBPTS was adequate to optimise balance results, reduce waiting time and makespan, and improve the utilisation of the resource in comparison to the current scheduling algorithms such as the particle swarm optimisation (PSO) and first come first serve (FCFS).</p>

Topics & Concepts

CloudSimComputer scienceJob shop schedulingBin packing problemDistributed computingCloud computingScheduling (production processes)CloudletDynamic priority schedulingFair-share schedulingMathematical optimizationBinOperating systemAlgorithmScheduleMathematicsCloud Computing and Resource ManagementScheduling and Optimization AlgorithmsIoT and Edge/Fog Computing
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