Puneet Sharma1, Dhirendra Prasad Yadav1, Bhisham Sharma2,*, Surbhi B. Khan3,4,*, Ahlam Almusharraf 5
CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 2179-2193, 2025, DOI:10.32604/cmc.2025.063190
- 29 August 2025
Abstract The swift expansion of cloud computing has heightened the demand for energy-efficient and high-performance resource allocation solutions across extensive systems. This research presents an innovative hybrid framework that combines a Quantum Tensor-based Deep Neural Network (QT-DNN) with Binary Bird Swarm Optimization (BBSO) to enhance resource allocation while preserving Quality of Service (QoS). In contrast to conventional approaches, the QT-DNN accurately predicts task-resource mappings using tensor-based task representation, significantly minimizing computing overhead. The BBSO allocates resources dynamically, optimizing energy efficiency and task distribution. Experimental results from extensive simulations indicate the efficacy of the suggested strategy; the… More >
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