Affiliations: Computer Science and Engineering, University College of Engineering Osmania University Hyderabad, India
Correspondence:
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Corresponding author: Prashant Balkrishna Jawade, Computer Science and Engineering, University College of Engineering Osmania University Hyderabad, India. E-mail: [email protected].
Abstract: The appliances that are received at a cloud data centre are a compilation of jobs (task) that might be independent or dependent on one another. These tasks are then allocated to diverse virtual machine (VM) in a scheduled way. For this task allocation, various scheduling policies are deployed with the intention of reducing energy utilization and makespan, and increasing cloud resource exploitation as well. A variety of research and studies were done to attain an optimal solution in a single cloud setting, however the similar schemes might not operate on multi-cloud environments. Here, this paper aims to introduce a secured task scheduling model in multi-cloud environment. The developed approach mainly concerns on optimal allocation of tasks via a hybrid optimization theory. Consequently, the developed optimal task allotment considers the objectives like makespan, execution time, security parameters (risk evaluation), utilization cost, maximal service level agreement (SLA) adherence and power usage effectiveness (PUE). For resolving this issue, a novel hybrid algorithm termed as rock hyraxes updated shark smell with logistic mapping (RHU-SLM) is introduced in this work. At last, the superiority of developed approach is proved on varied measures.
Keywords: Task allocation, multi-cloud, makespan, power usage, RHU-SLM model
