Load balancing on cloud using professional service scheduler optimization

Abstract

In smart grid (SG) fog computing based concept is used. Fog is used to minimizing the load on cloud. It stores data temporarily by covering small area and send data to cloud for permanent storage. In this paper, cloud and fog are integrated for the better execution of energy in the smart building. In our proposed framework from interest side a demand created which oversaw by haze. Three unique districts which contains six mists. Fog is associated with a cluster. Include the quantities of structures each fog is associated with each fog. Each cluster contained thirty buildings and each building comprises of 10 homes. SGs are put close to the buildings and used to satisfy energy request. These SGs are set adjacent to the buildings. For productive use of vitality in smart buildings, Virtual Machines (VMs) are used to overcome the load on fog and cloud. Throttled, Round Robin (RR) and Professional Service Scheduler (PSS) are used as load balancing algorithms and these algorithms are compared for closest data center service broker policy. It is used for best fog selection. Using this policy the results of these algorithms are compared. Cost wise policy outperforms are shown. However, RR and throttled performing better overall.