Providing an Effective Network Load Balancing Algorithm to Improve the Efficiency of the Cloud Computing System based on Memetic

Cloud computing is a large distributed system that utilizes distributed resources to provide a service to the end-user through the implementation of several technologies. A distributed system often involves heterogeneous communication and computing resources. Given the differences in computational capacities and patterns of inactivity, the workload on the various computer systems can vary greatly. Load balancing is one of the fundamental challenges in cloud computing, which we can use to combine several efficient algorithms according to our needs. But cloud computing covers a wide range of domains. Therefore, it is necessary to develop a comparative algorithm that is suitable for heterogeneous environments and reduces costs. Math modeling the strategic situation in the cloud computing load balancing problem with the help of the Memetic algorithm to satisfy multiple conflicting objectives such as cost reduction, efficiency and reduction of response time, which are particularly important in time-sensitive applications, are critical. In this study, the load balancing in the cloud was investigated using the memetic algorithm, a kind of hybrid genetic algorithm, and examined by a genetic comparison in the field of cultural evolution, which is now one of the growing spaces in research in evolutionary computing. And the results have been compared with some of the work done in this area. The results of the proposed algorithm show that the use of the mantle algorithm for the number of times the implementation can optimally balance the load and reduce the average waiting time to receive the response.

Providing an Effective Network Load Balancing Algorithm to Improve the Efficiency of the Cloud Computing System based on Memetic Keywords:

Network Load Balancing Algorithm , Efficiency of the Cloud Computing System , Memetic