Nature inspired meta-heuristic algorithms for solving the load-balancing problem in cloud environments

摘要

In a cloud environment, the aim of using optimal resources can be achieved using a load-balancing technique. The load-balancing technique assigns a set of requests into a set of resources for distributing the load. It is one of the significant issues in cloud computing and known as an NP-hard problem. Therefore, many nature-inspired meta-heuristic techniques are proposed to provide high efficiency. However, despite the importance of the nature-inspired meta-heuristic techniques for solving the problem of the load-balancing in the cloud environment, there is not a complete and detailed paper about reviewing and studying the main important issues in this domain. Therefore, this paper presents comprehensive coverage of the nature-inspired meta-heuristic techniques applied in the area of the cloud load-balancing. The main goal of this paper is to highlight the emphasis on optimization algorithms and the benefits that they provide to overcome the cloud load-balancing challenges. In addition, to solve the load-balancing problem in the cloud environments, the advantages and disadvantage of the nature-inspired meta-heuristic algorithms have been analyzed and their significant challenges are considered for proposing the techniques that are more effective in the future. (C) 2019 Elsevier Ltd. All rights reserved.