A novel resource clustering model to develop an efficient wireless personal cloud environment

Abstract

In the current era, cloud computing is the major focus of distributed computing and it helps in satisfyingthe requirements of the business world. It provides facilities on demand under all the parameters of the computing, suchas infrastructure, platform, and software, across the globe. One of the major challenges in the cloud environment is tocluster the resources and schedule the jobs among the resource clusters. Many existing approaches failed to provide anoptimal solution for job scheduling due to inefficient clustering of resources. In the proposed system, a novel algorithmcalled resource differentiation based on equivalence node potential (RDENP) is proposed for clustering the resources ina simulated wireless personal cloud environment. The performance evaluation is done among the existing and proposedapproaches; as a result, the proposed RDENP algorithm produces the optimal solution for clustering the resources,which will lead to an efficient scheduling policy in a cloud environment in the future. To take this idea forward, anoptimal energy consumption algorithm is to be designed to process the jobs among the resources and to minimize theinfrastructure of the cloud environment by clustering the resources virtually.