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A Hybrid Metaheuristic Approach for Optimizing Resource Allocation in Cloud Computing Environments

Authors: Dr. Shabana Faizal

Published: 2025-05-02 10:46:02.521

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Abstract

Cloud computing environments offer on-demand access to a shared pool of configurable computing resources. Efficient resource allocation is crucial for maximizing performance, minimizing costs, and ensuring quality of service. This paper proposes a novel hybrid metaheuristic approach for optimizing resource allocation in cloud environments. The approach combines the strengths of the Genetic Algorithm (GA) and Simulated Annealing (SA) to achieve a superior balance between exploration and exploitation of the search space. The GA is used for global exploration, identifying promising regions of the solution space, while SA is employed for local refinement, fine-tuning solutions within those regions. The proposed hybrid algorithm is evaluated through simulations on a cloud environment, and the results demonstrate its effectiveness in minimizing resource utilization, reducing makespan, and improving overall system performance compared to traditional GA and SA algorithms. The results highlight the potential of the hybrid approach for practical applications in cloud resource management.

Keywords

Cloud Computing, Resource Allocation, Optimization, Metaheuristics, Genetic Algorithm, Simulated Annealing, Hybrid Algorithm, Virtual Machines, Load Balancing, Performance

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How to Cite

Dr. Shabana Faizal, (2025-05-02 10:46:02.521). A Hybrid Metaheuristic Approach for Optimizing Resource Allocation in Cloud Computing Environments. JANOLI International Journal of Applied Engineering and Management, Volume UIh3MC5UrwhGKptS6jkQ, Issue 3.

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