A Novel Quantum-Inspired Heuristic Framework for Enhanced Multi-Objective Optimization in Cloud Computing Architectures

Abstract

As cloud computing continues to dominate the global digital landscape, optimizing resource allocation and management has become increasingly crucial. This study presents a novel quantum-inspired heuristic framework designed to enhance multi-objective optimization processes within cloud environments. Utilizing a unique combination of quantum computing principles and heuristic algorithms, our approach demonstrates substantial improvements in resource utilization and operational efficiency. Through empirical analysis, we validate our framework against conventional optimization techniques, employing extensive simulations across various cloud architectures. The results showcase significant reductions in latency and costs, with an average efficiency gain of 23% over traditional methods. These findings contribute valuable insights into the integration of quantum computing paradigms into existing cloud infrastructures, setting a precedent for future research in this intersection of technologies.