TY - JOUR
AU1 - Asghari, Saied
AU2 - Jafari Navimipour, Nima
AB -  There are many issues and problems in cloud computing that researchers try to solve by using different techniques. Most of the cloud challenges are NP-hard problems; therefore, many meta-heuristic techniques have been used for solving these challenges. As a famous and powerful meta-heuristic algorithm, the Ant Colony Optimisation (ACO) algorithm has been recently used for solving many challenges in the cloud. However, in spite of the ACO potency for solving optimisation problems, its application in solving cloud issues in the form of a review article has not been studied so far. Therefore, this paper provides a complete and detailed study of the different types of ACO algorithms for solving the important problems and issues in cloud computing. Also, the number of published papers for various publishers and different years is shown. In this paper, available challenges are classified into different groups, including scheduling, resource allocation, load balancing, consolidation, virtual machine placement, service composition, energy consumption, and replication. Then, some of the selected important techniques from each category by applying the selection process are presented. Besides, this study shows the comparison of the reviewed approaches and also it highlights their principal elements. Finally, it highlights the relevant open issues and some clues to explain the difficulties. The results revealed that there are still some challenges in the cloud environments that the ACO is not applied to solve. 
TI - The role of an ant colony optimisation algorithm in solving the major issues of the cloud computing
JF - Journal of Experimental & Theoretical Artificial Intelligence
DO - 10.1080/0952813X.2021.1966841
DA - 2023-08-18
UR - https://www.deepdyve.com/lp/taylor-francis/the-role-of-an-ant-colony-optimisation-algorithm-in-solving-the-major-qw33tD4YZc
SP - 755
EP - 790
VL - 35
IS - 6
DP - DeepDyve
ER -