Quantum-Inspired Heuristic Optimization for Large-Scale Cloud Resource Allocation
Journal: International Journal of Science and Research (IJSR) (Vol.11, No. 10)Publication Date: 2022-10-05
Authors : Manuja Sanjay Bandal;
Page : 1477-1481
Keywords : Cloud computing; quantum-inspired algorithms; heuristic optimization; resource allocation; distributed systems;
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.
Other Latest Articles
- End-to-End MLOps in Financial Services: Resilient Machine Learning with Kubernetes
- AI-Powered Insider Threat Detection with Behavioral Analytics with LLM
- Predicting Soccer Match Outcomes Using Deep Learning: A Long Short-Term Memory (LSTM) Approach
- SD - WAN Technology: Advantages and Use Cases
- Improving Client Relations through Transparent Communication and Strategic Planning: How Effective Communication and Strategic Foresight Helped Build Strong Client Relationships
Last modified: 2025-09-22 21:31:24