AN EFFICIENT RESOURCE SELECTION AND ALLOCATION IN CLOUD COMPUTING USING ARTIFICIAL NUTRIENTS DISTRIBUTION MODEL

Abstract

The recent emergence of cloud computing and its rapid advancement in recent time indicates a promising technology. However, the increasing number of providers with different policies has induced a challenge for customers to select providers that can efficiently satisfy their requirements. This research work is regarding resource selection and allocation in cloud computing using artificial nutrients distribution model. Cloud computing makes it possible for system administrators to allocate resources whenever it is required. It provides multiple servers that are expandable and can meet future needs without buying any physical computer equipment. Because there are lots of providers available commercially selection of resources from reliable provider has become difficult for cloud users. This research proposed a new intelligent model using the idea of nutrients distribution in human body to optimally select and allocate resources in cloud. This model enables users to efficiently select resources from the integrated providers as a single unit of resource pool. The model intelligently evaluates the available resources from different providers and expeditiously selects a resource of highest value for the customer. This research has designed an intelligent architecture, algorithm and the UML model for Resource Selection, Evaluation and allocation. The simulation showed that the overhead cost of searching from one provider to another as opposed to the existing methods is minimized. This model is of good quality and could obtain solution with a worthy efficiency by only making a single selection attempts as providers’ resources are interwoven to a single resource pool.