Summative Score based Virtual Machine Instance Allocation in Cloud Computing
P Karthikeyan, M Chandrasekaran · Asian Journal of Research in Social Sciences and Humanities · 2016
Virtual machine instance allocation refers to the mapping an enormous number of the virtual machines instance to an enormous number of users. Existing Greedy algorithm assigns the virtual machines instance to the users according to bid density or a product of resource factors, which will probably lead to an imbalance of the virtual machine instance allocation. We propose a summative score based virtual machine instance allocation model to rank the users, to improve virtual machine instance allocation. The main aim of this algorithm is to maximize the cloud provider's social welfare value. We assess the proposed algorithm performance by performing simulations. The experimental result sclearly illustrate that the proposed summative score based virtual machine instance allocation offer a higher revenue for the cloud provider than traditional greedy method.