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Multi-objective constraint and hybrid optimisation-based VM migration in a community cloud
Multi-objective constraint and hybrid optimisation-based VM migration in a community cloud
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Multi-objective constraint and hybrid optimisation-based VM migration in a community cloud
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Multi-objective constraint and hybrid optimisation-based VM migration in a community cloud
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Multi-objective constraint and hybrid optimisation-based VM migration in a community cloud
Multi-objective constraint and hybrid optimisation-based VM migration in a community cloud
Journal Article

Multi-objective constraint and hybrid optimisation-based VM migration in a community cloud

2020
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Overview
The growing demand for the cloud community market towards attracting and sustaining the incoming and the available cloud users is addressed actively to meet the competitive environment. There is a good scope for improving the provider capabilities in the cloud in order to satisfy the users with attractive benefits. The study introduces an effective virtual machine (VM) migration strategy using an optimisation algorithm in such a way to facilitate the user selection of the providers based on their budgetary requirements in running their own platforms. The constraints associated with the selection of the provider include cost, revenue, and resource, which are altogether confined as an elective factor. The optimisation algorithm employed for the VM migration is referred to as Taylor series-based salp swarm algorithm (Taylor-SSA) that is the integration of the Taylor series with SSA. The evaluation of the method is progressed using three setups by varying the number of providers and users. The cost, the revenue, and the resource of the proposed method are analysed and concluded that the proposed method acquired a minimal cost, maximal resource gain and revenue.