Goal: Load balancing policies often map workloads on virtual machines, and are being sought to achieve their goals by creating an almost equal level of workload on any virtual machine. In this research, a hybrid load balancing algorithm is proposed with the aim of reducing response time and processing time.
Design / Methodology / Approach: The proposed algorithm performs load balancing using a table including the status indicators of virtual machines and the task list allocated to each virtual machine. The evaluation results of response time and processing time in data centers from four algorithms, ESCE, Throttled, Round Robin and the proposed algorithm is done.
Results: The overall response time and data processing time in the proposed algorithm data center are shorter than other algorithms and improve the response time and data processing time in the data center. The results of the overall response time for all algorithms show that the response time of the proposed algorithm is 12.28%, compared to the Round Robin algorithm, 9.1% compared to the Throttled algorithm, and 4.86% of the ESCE algorithm.
Limitations of the investigation: Due to time and technical limitations, load balancing has not been achieved with more goals, such as lowering costs and increasing productivity.
Practical implications: The implementation of a hybrid load factor policy can improve the response time and processing time. The use of load balancing will cause the traffic load between virtual machines to be properly distributed and prevent bottlenecks. This will be effective in increasing customer responsiveness. And finally, improving response time increases the satisfaction of cloud users and increases the productivity of computing resources.
Originality/Value: This research can be effective in optimizing the existing algorithms and will take a step towards further research in this regard.
Proposing a load balancing algorithm with an integrative approach to reduce response time and service process time in data centers