A review of load balancing algorithms in cloud computing environment

The instantaneous increase in users and their need for internet services caused that, in a short time, the companies that provided this type of service faced problems such as the inability to respond quickly to users and the increase in their costs. Therefore, many of these companies, with a lot of investments in research fields, thought of effective and cost-effective ways to serve a high volume of users, and in this way, new technology and an efficiency system called cloud computing were created. With the increase in users using cloud computing services and therefore the increase in the number of requests, in order to achieve the mentioned benefits, there is a need to establish appropriate mechanisms for load balancing, work scheduling and virtualization. Sazi is in cloud computing. This load can include memory capacity, network load or delay. Load balancing is the process of distributing load among different nodes of a distributed system in order to improve the utilization of resources and response time, while it is a situation in which some nodes have a heavy load while the node Others avoid being unemployed or having very little work to do. Considering the necessity and importance of load balancing in cloud computing, in this article, a comprehensive review of static, dynamic and nature-inspired algorithms for load balancing in a cloud space to handle the response time of data centers and their overall performance is given. We pay by analyzing the load balancing algorithms. We show that the ant colony algorithm, the genetic algorithm and the particle swarm optimization algorithm with optimal allocation of tasks can play a more effective role in balancing the load in the cloud space. Also, the results show that CloudSim software has been used the most in simulating load balancing algorithms in the cloud space.