Allocation of resources for user requests or scheduling jobs for multiple computing resources in the cloud environment is a significant task in the cloud date center because it is associated with cost. The objective of load balancing is to detect overloaded and underloaded nodes and then balance the load among them. Load balancing takes the advantages of scalability and provides measure to check the applications performance. In order to maintain low overhead in the cloud service providers side, the scheduling and balancing mechanism is to be implemented in decentralized manner. By taking advantages of meta-heuristic algorithms, the load balancing is assumed as objective function and work on for improving results or to find best fitness value for the function. In this study, the same can be investigated thoroughly using different meta-heuristic approaches; its outcomes are analyzed and concluded.
S. Sundararajan and C.R. Sakthivel. Certain Investigation on Variants of Load Balancing in Big Data Centers using Meta-Heuristic
Algorithms.
DOI: https://doi.org/10.36478/ajit.2020.91.94
URL: https://www.makhillpublications.co/view-article/1682-3915/ajit.2020.91.94