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Blockchain-Based Collaborative Task Offloading Algorithm in Heterogeneous Edge Computing Networks
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AI
DOI：10.1109/TCCN.2025.3564502.png)
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Abstract
En 中文
With the increasing complexity and diversity of modern computing environments, the collaborative capabilities of heterogeneous edge computing networks have become essential in meeting diverse user needs and enhancing overall network performance. However, due to concerns over data privacy, security, and the technical standards and protocols unique to each network node, nodes are often reluctant to share their computational resources and information. This issue significantly restricts the collaborative capacity and system efficiency of edge computing networks. To address this challenge, we propose a Blockchain-Based Collaborative Task Offloading Algorithm in Heterogeneous Edge Computing Networks (BCTOH). By introducing blockchain technology, the algorithm ensures resource and data security among heterogeneous edge nodes. Additionally, it deploys a Collaborative Reinforcement Learning (CRL) algorithm across heterogeneous network nodes, facilitating resource information sharing, cooperation, and distributed task offloading training. This approach breaks down trust barriers between heterogeneous edge nodes, reducing latency and energy consumption in task offloading and improving service quality and system reliability. Simulation results demonstrate that the proposed BCTOH algorithm effectively coordinates task offloading among heterogeneous edge nodes, optimizing system latency and energy consumption and significantly enhancing overall network performance.
Keywords:
Blockchain
heterogeneous networks
edge computing
task offloading
collaborative reinforcement learning
Journal
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7
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1.5K
Citations:
5.5K