Load balancing techniques in cloud computing: A review

Abstract

Cloud computing provides an easy and flexible accessibility of resources on the Internet. In this case the clients can use the available resources as they need without upgrading their own hardware.   Thus, load balancing is considered as one of the most challenging issues related to the cloud computing where multiple tasks (processes) must be run simultaneously on the processing elements. There are different algorithms used for the task’s allocation on those elements. The tasks can be distributed according to different schemes. Some algorithms suggest prioritizing the tasks while some others distribute the balance according to the length of the task. However, there is a large number of the load balancing methods that depends on the Artificial Intelligence techniques. Specifically, the utilization of the meta-heuristic algorithms for the task’s distribution on the virtual machines. The aim of these algorithms is to enhance the cloud system productivity by looking for the optimal distribution of those tasks on the virtual machines. There is a large number of methodologies that is worthy to review and investigate in terms of their efficiency, performance and productivity. The main aim of this work is to make a comprehensive literature review paper that discuss the advancement of this area through the years. The advantages and disadvantages of those methods are investigated in order to highlight the gaps and try to suggest some solutions in future. In addition, the classification is conducted on basis of the parameter coefficients. Besides, a full analysis has been made for the compared methods. The futuristic aspects of the utilization of the currently used load balancing algorithms has also been highlighted.