ABSTRACT
The distribution of the workload of all incoming requests over the cloud-based data centers is big issue in the present-day scenario. The cloud provides several services to handle the different resources and applications for distributing the entire requests as per the requirements through multiple data centers. The number of requests is increasing daily over the data centers; at the same time exchanging the request and response faces more complexity to handle the potential overloading of the data centers. It also gives the negative impact on the quality of service of cloud services. The measurement of user application performance of several resources is a challengeable task to solve this type of problem due to requirement of different configuration of the user’s system. There are several load-balancing approaches and algorithms which have been implemented for cloud-based distributed data centers. In addition, the scheduling and broker policy algorithms are a major factor in solving the issues related to workload handling in cloud-based distributed data centers. In this research, we studied several issues related to overloading over the cloud-based data centers and also analyzed the scheduling and load-balancing algorithms to help the data center to balance the load based on different parameters evaluated by the Cloud Analyst Simulation Tool. This research gives the positive result of using the scheduling and broker policy algorithms to present better performance in terms of response time and data transfer cost in the cloud environment. In this research, we propose a Distributed Service Broker Policy Algorithm (DSBP) and compared it with an existing algorithm, the Crow Search Based Load Balancing Algorithm (CSLBA), which selects the best resource to time calculation over the cloud-based data center.
