A HYBRID METAHEURISTIC OPTIMIZATION APPROACH FOR ENERGY-EFFICIENT RESOURCE ALLOCATION IN EDGE–CLOUD COMPUTING ENVIRONMENTS
Keywords:
Edge Computing, Cloud Computing, Resource Allocation, Genetic Algorithm, Particle Swarm Optimization, Energy Efficiency, Metaheuristic Optimization.Abstract
The rapid growth of Internet of Things (IoT) applications, real-time analytics, and latency-sensitiveservices has significantly increased the demand for efficient resource management in edge–cloud computingenvironments. Edge computing extends computational capabilities closer to end users, while cloud computing provides scalable storage and processing resources
References
James Kennedy and Russell Eberhart, “Particle Swarm Optimization,” Proceedings of IEEE International Conference on Neural Networks, pp. 1942–1948, 1995.
David E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, Reading, MA, USA: Addison-Wesley, 1989.
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Published
2024-02-15
How to Cite
Kumbala Pradeep Reddy , B. Narendra Kumar,S Jagadeesh. (2024). A HYBRID METAHEURISTIC OPTIMIZATION APPROACH FOR ENERGY-EFFICIENT RESOURCE ALLOCATION IN EDGE–CLOUD COMPUTING ENVIRONMENTS . Journal of Computational Analysis and Applications (JoCAAA), 32(2), 814–823. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5551
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