Adaptive Quantum-Inspired Algorithms for Efficient Resource Allocation in Cloud Computing Environments
Keywords:
Cloud Computing, Quantum-Inspired Algorithms, Resource Allocation, Performance Optimization, Heuristic Methods, Data Processing, Computational Efficiency, Virtual MachinesAbstract
With the rapid adoption of cloud computing, efficient resource allocation remains a significant challenge. This study harnesses quantum-inspired algorithms to optimize resource distribution, enhancing virtual machine performance while minimizing latency. Employing a hybrid approach, we simulate scenarios in MATLAB, incorporating a range of computational loads and usage patterns. Our empirical findings indicate a remarkable 25% reduction in response time compared to existing heuristic methodologies, alongside consistent improvements in resource utilization rates. These results establish a viable pathway for integrating quantum computing principles into current cloud infrastructures, promoting sustainability and cost-efficiency.
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