HBPSO based Resource Scheduling for Optimization of Cost and Makespan in Cloud Data Centers

Now present years, Cloud computing has emerged as a computational model for High-Performance Computing (HPC) applications, which deals with complex and highly intensive data. Cloud computing is a promising new style of scheduling environment which provides an scalable with on-demand supply methods to the consumers. In a cloud context, job or application scheduling is difficult and NP-complete. The objective of this work is to develop an algorithm to schedule for efficiently managing cloud resources besides finishing jobs with scientific applications applied in the Cloud Resource Broker (CRB) framework in Cloud Data Centre (CDC). The proposed HoneyBee based PSO (HBPSO) scheduling algorithm is deliberated for efficient resource allocation and henceforth the suggested optimization method anticipates to accomplish the objectives in minimizing both execution time and cost required to execute the job. It promotes resource allocation and job scheduling functions by balancing the load and reducing the skew, this in turn will eventually decrease cost, make span and resource utilization. Our goal is to transform the cloud datacenter to an efficient and effective datacenter in terms of time, cost and resource utilization so as to enhance the business values. By reducing completion times and costs while increasing the number of applications completed and user satisfaction, the simulation results utilizing Cloudsim and Cloud analyst demonstrate the efficacy of the suggested research work.