A Performed Load Balancing Algorithm for Public Cloud Computing Using Ant Colony Optimization

Background: In the space of a few years, Cloud computing has experienced remarkable growth. Indeed, its economic model based on demand use of hardware and software according to technical criteria such CPU utilization, memory, and bandwidth or package has strongly contributed to the liberalization of computing resources in the world. However, the development of Cloud computing requires the optimization of the performance of the different services offered by Cloud providers to ensure a high level of security, availability, and responsiveness. One major aspect of dealing with performance issues in Cloud computing is the load balancing. In fact, an efficient load balancing contributes to cost decrease and maximizes the availability of resources. Objective: In this paper, we aim to propose an enhanced load balancing strategy to improve the Cloud performance. This paper includes a comparative study of the previous research works conducted in the area of load balancing in the Cloud computing. Method: This research work introduces a global analysis of Cloud computing model that applies the Taguchi concept to highlight the parameters which have the greatest impact on the system performance. Finally, we propose a load balancing system to ensure an efficient response time with the lowest cost. Results: The proposed architecture has demonstrated an improvement in response time and processing time. The simulations carried out within CloudAnalyst platform showed an improvement of almost 11% of the response time recorded by the proposed ant colony algorithm compared to the response time achieved by the Round robin algorithm and improvement of the processing time by nearly 38%. Conclusion: We conclude this article by the potential application of the performance methodology applied and the proposed ant colony algorithm to improve the performance of the Cloud environment.