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Cloud computing distributes computing tasks across numerous distributedresources for large-scale calculation. The task scheduling problem is along-standing problem in cloud-computing services with the purpose ofdetermining the quality, availability, reliability, and ability of the cloudcomputing. This paper is an extension and a correction to our previousconference paper entitled Multi Objective Scheduling in Cloud Computing UsingMOSSO published in 2018 IEEE Congress on Evolutionary Computation. More newalgorithms, testing, and comparisons have been implemented to solve thebi-objective time-constrained task scheduling problem in a more efficientmanner. Furthermore, this paper developed a new SSO-based algorithm called thebi-objective simplified swarm optimization to fix the error in previousSSO-based algorithm to address the task-scheduling problem. From the resultsobtained from the new experiments conducted, the proposed BSSO outperformsexisting famous algorithms, e.g., NSGA-II, MOPSO, and MOSSO in the convergence,diversity, number of obtained temporary nondominated solutions, and the numberof obtained real nondominated solutions. The results propound that the proposedBSSO can successfully achieve the aim of this work.

A new SSO-based Algorithm for the Bi-Objective Time-constrained task Scheduling Problem in Cloud Computing Services