Quantum-Enhanced, AI-Driven, and Privacy-Compliant Scheduling Framework for Healthcare in Distributed Cloud-Edge Environments

Abstract

Emergence of new innovative healthcare applications such as telemedicine, wearable diagnostics or real-time patient monitoring, bring additional challenges by forcing to develop new task scheduling mechanisms that can mitigate various dynamics of workloads, allow for low-latency processing, be energy efficient, and comply with tight data privacy regulations. Also, conventional centralized scheduling schemes are no longer sufficient to solve these multidimensional problems, especially in distributed edge-cloud scenarios. In this paper, we present a new integrated hybrid scheduling model that incorporates artificial intelligence (AI), quantum-inspired algorithms, federated learning, and blockchain, in order to bridge existing healthcare task orchestration challenges. Our contributions are: (1) AI-driven predictive models based on analytics to predict healthcare demand and optimize resource allocation; (2) quantum-inspired scheduling to address NP-hard optimization problems, including diagnostic task prioritization; (3) adaptive edge scheduling with explicit support for federated learning to enable real-time, low-latency operations; (4) privacy-aware task orchestration using blockchain to keep the data secure and audit data sharing; and (5) energy-efficient algorithms for dynamic workload balancing over heterogeneous cloud-edge systems. Extensive simulations indicate that the proposed approach outperforms its existing counterparts in terms of numerous standard performance metrics like task completion time, energy consumption, system throughput, and scheduling accuracy. Empirical results on real-world and synthetic healthcare datasets demonstrate that we are able to achieve better responsiveness and scalability and at the same time satisfy privacy in GDPR and HIPAA. The combination of quantum-inspired models together with federated and blockchain-based learning establishes a new era of intelligent, secure, as well as sustainable healthcare infrastructure.