Using Harmony Search Algorithm for Load Balancing in Cloud Computing

Abstract

Background: In this paper, we have surveyed the load modification and the trust capability in the cloud computing data centers. Method: The components of harmony search Algorithm include the harmony memory, the pitch adjustment rate and the random selection. The harmony memory checks and selects the responses. HMCR (Harmony Memory Considering Rate) is used for showing the possibility of selection from the memory and the pitch adjustment rate is used for causing a new harmony. Findings: Standard deviation and the resource exploitation average are the most important criteria at the load balancing. In this paper, the proposed Algorithm has been compared with the Genetic Algorithm and the simulation results show that the proposed Algorithm has a better competence than the Genetic Algorithm as the HSD (Harmony Search Degertekin ) rate of the proposed method is less than the HSD rate of Genetic Algorithm and the average of utilization from resources in the proposed method is more as well as with the increasing number of tasks, the performance of the algorithm is improved. Application/Improvement: Using this method of load balancing, the satisfaction of users is maximized, the time of response is minimized and the utilization of resources is increased.