Artificial bee colony with map reducing technique for solving resource problems in clouds

Abstract

Background/Objectives: Overseeing resources at mega scale while giving performance isolation and efficient utilization of basic hardware is a key test for any cloud management software. Aside from scalability issue, a cloud-level resource management layer requirements to settle the heterogeneity of frameworks, compatibility imperatives between virtual machines and basic hardware, islands of resources made because of storage and network connectivity and restricted scale of storage resources. Methods/Statistical Analysis: Upshots prospects promising optimizable brooks initiated probe in various filed, in this work we projected an effectual topology for solving the resource model for resource problem solution. Deployment of optimization algorithm opted for multi objective problem is Artificial Bee Colony Algorithm (ABC) which delivered best optimized result and less computation time is utilized to unfurl the determined objective, upshots of the proposition topology has depicted promising and effectual results and minimized computational exertion. Findings: In our proposed method, the execution time is reduced largely when compared to the existing method. Applications/ Improvements: Optimization of cloud computing resource utilization.