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In the current era, cloud computing is the major focus of distributed computing and it helps in satisfying the requirements of the business world. It provides facilities on demand under all the parameters of the computing, such as infrastructure, platform, and software, across the globe. One of the major challenges in the cloud environment is to cluster the resources and schedule the jobs among the resource clusters. Many existing approaches failed to provide an optimal solution for job scheduling due to inefficient clustering of resources. In the proposed system, a novel algorithm called resource differentiation based on equivalence node potential (RDENP) is proposed for clustering the resources in a simulated wireless personal cloud environment. The performance evaluation is done among the existing and proposed approaches; 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, an optimal energy consumption algorithm is to be designed to process the jobs among the resources and to minimize the infrastructure of the cloud environment by clustering the resources virtually.

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