MG-CS: Micro-Genetic and Cuckoo Search Algorithms for Load-Balancing and Power Minimization in Cloud Computing

Cloud computing has emerged as a transformative technology, offering remote access to various computing resources. However, efficiently managing these resources while curbing escalating energy consumption remains a critical challenge. In response, this paper presents the Micro-Genetic Algorithm with Cuckoo Search (MG-CS), a novel approach for enhancing cloud computing efficiency. MG-CS optimizes load balancing and power reduction and significantly contributes to reducing operational costs, ensuring compliance with service level agreements, and enhancing overall service quality. Our experiments showcase MG-CS's versatility in achieving a well-balanced distribution of workloads, resource optimization, and substantial energy savings. This multifaceted approach redefines cloud resource management, offering an environmentally sustainable and cost-effective solution. By introducing MG-CS, this research addresses the pressing challenges in cloud computing, aligning it with environmental responsibility and economic efficiency.

@article{ZHOU2023,
  title     = {MG-CS: Micro-Genetic and Cuckoo Search Algorithms for Load-Balancing and Power Minimization in Cloud Computing},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {14},
  number    = {11},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Jun ZHOU and Youyou Li},
  doi       = {10.14569/IJACSA.2023.01411117},
  url       = {https://doi.org/10.14569/IJACSA.2023.01411117}
}