Improved Cat Swarm Optimization Algorithm for Load Balancing in the Cloud Computing Environment

Recently, cloud computing has gained recognition as a powerful tool for providing clients with flexible platforms, software services, and cost-effective infrastructures. Cloud computing is a form of distributed computing that allows users to store and process data in a virtual environment instead of a physical server. This is beneficial because it allows businesses to quickly scale up or down their computing capacity, reducing the need to invest in expensive hardware. As cloud tasks continue to grow exponentially and the usage of cloud services increases, scheduling these tasks across diverse virtual machines poses a challenging NP-hard optimization problem with substantial requirements, including optimal resource utilization levels, a short execution time, and a reasonable implementation cost. The issue has consequently been addressed using a variety of meta-heuristic algorithms. In this paper, we propose a new load-balancing approach using the Cat Swarm Optimization (CSO) algorithm in order to distribute the load among the various servers within a data center. Statistical analyses indicate that our algorithm is superior to previous research with regard to energy consumption, makespan, and time required up to 30%, 35%, and 40%, respectively.

@article{Dou2023,
  title     = {Improved Cat Swarm Optimization Algorithm for Load Balancing in the Cloud Computing Environment},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {14},
  number    = {7},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Wang Dou},
  doi       = {10.14569/IJACSA.2023.01407112},
  url       = {https://doi.org/10.14569/IJACSA.2023.01407112}
}