Junjie Cao1,2, Zhiyong Yu2,*, Xiaotao Xu1, Baohong Zhu3, Jian Yang2
CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5235-5257, 2025, DOI:10.32604/cmc.2025.062371
- 19 May 2025
Abstract This paper introduces a quantum-enhanced edge computing framework that synergizes quantum-inspired algorithms with advanced machine learning techniques to optimize real-time task offloading in edge computing environments. This innovative approach not only significantly improves the system’s real-time responsiveness and resource utilization efficiency but also addresses critical challenges in Internet of Things (IoT) ecosystems—such as high demand variability, resource allocation uncertainties, and data privacy concerns—through practical solutions. Initially, the framework employs an adaptive adjustment mechanism to dynamically manage task and resource states, complemented by online learning models for precise predictive analytics. Secondly, it accelerates the search for… More >
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