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Research Paper | Computer Science Engineering | Volume 11 Issue 10, October 2022 | Pages: 1477 - 1481 | United States
Quantum-Inspired Heuristic Optimization for Large-Scale Cloud Resource Allocation
Abstract: Efficient cloud resource allocation remains a critical challenge in large-scale distributed computing environments. Traditional heuristic methods, such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), have limitations in terms of convergence speed and optimality. Inspired by quantum computing principles, we propose a Quantum-Inspired Heuristic Optimization (QIHO) approach that enhances cloud resource allocation efficiency. By leveraging quantum superposition and interference properties, our approach improves search space exploration and convergence rates. Experimental evaluations demonstrate a 25% reduction in computational overhead and a 30% improvement in resource utilization compared to conventional heuristics.
Keywords: Cloud computing, quantum-inspired algorithms, heuristic optimization, resource allocation, distributed systems
How to Cite?: Manuja Sanjay Bandal, "Quantum-Inspired Heuristic Optimization for Large-Scale Cloud Resource Allocation", Volume 11 Issue 10, October 2022, International Journal of Science and Research (IJSR), Pages: 1477-1481, https://www.ijsr.net/getabstract.php?paperid=SR221011091902, DOI: https://dx.doi.org/10.21275/SR221011091902