Hybrid Quantum–Cloud Framework for Nonlinear Clustering Optimization and Intelligent Resource Management

Abstract

This paper proposes a hybrid quantum-cloud computing architecture, which ought to be applied to overcome the two problems of nonlinear clustering optimization and intelligent management of large-scale resources in the heterogeneous environments. The current cloud workloads in terms of complexity, scalability, and energy needs are not always easily met by the conventional machine learning and heuristic scheduling processes, particularly in cases where the data possess nonlinear structures. These weaknesses will be mitigated by the proposed framework that will integrate quantum-inspired algorithms (which will operate on variational quantum circuits and Quantum Approximate Optimization Algorithm (QAOA)) with cloud-native orchestration solutions, only that reinforcement learning-based scheduling will be integrated. This architecture has its quantum layer where nonlinear clustering is done to achieve more accurate workload partitioning, and cloud layer sharing resources and balancing throughput, latency, and energy efficiency. It is a broker interface that provides a fluent communication between quantum processors and cloud infrastructure that makes it possible to make real time decisions. The synthetic nonlinear clustering, IoT workloads and big data traces benchmark datasets were experimentally simulated on CloudSim and Kubernetes. Results indicate that the framework can lead to a significant performance increase as compared to conventional approaches and that the accuracy of the clustering process has been enhanced by 12-18, average job latency has been reduced by 22 and resource utilization efficiency has been improved by 25. Additionally, the hybrid approach is very scalable and stable as the degree of workload varies and is able to support quality-of-service (QoS) even during the peak period of workload. In these studies, the findings show the possibility of quantum and cloud computing hybridization to the next generation of intelligent cloud eco-systems to give a pathway to green, flexible, and high-performance computing in the current areas, 6G networks, smart cities, bioinformatics, and smart financial analytics.