5G networks provide secure and reliable information transmission services for the Internet of Everything, thus paving the way for 6G networks, which is anticipated to be an AI-based network, supporting unprecedented intelligence across applications. Abundant computing resources will establish the 6G Computing Power Network (CPN) to facilitate ubiquitous intelligent services. In this article, we propose BECS, a computing sharing mechanism based on evolutionary algorithm and blockchain, designed to balance task offloading among user devices, edge devices, and cloud resources within 6G CPN, thereby enhancing the computing resource utilization. We model computing sharing as a multi-objective optimization problem, aiming to improve resource utilization while balancing other issues. To tackle this NP-hard problem, we devise a kernel distance-based dominance relation and incorporated it into the Non-dominated Sorting Genetic Algorithm III, significantly enhancing the diversity of the evolutionary population. In addition, we propose a pseudonym scheme based on zero-knowledge proof to protect the privacy of users participating in computing sharing. Finally, the security analysis and simulation results demonstrate that BECS can fully and effectively utilize all computing resources in 6G CPN, significantly improving the computing resource utilization while protecting user privacy.

翻译：5G网络为万物互联提供了安全可靠的信息传输服务，从而为6G网络奠定了基础。6G网络预计将成为基于人工智能的网络，支持跨应用的前所未有的智能化。丰富的计算资源将构建6G算力网络，以促进无处不在的智能服务。本文提出BECS，一种基于进化算法和区块链的计算共享机制，旨在平衡6G算力网络内用户设备、边缘设备和云资源之间的任务卸载，从而提高计算资源利用率。我们将计算共享建模为一个多目标优化问题，旨在提高资源利用率的同时平衡其他问题。为解决这一NP难问题，我们设计了一种基于核距离的支配关系，并将其纳入非支配排序遗传算法III，显著增强了进化种群的多样性。此外，我们提出了一种基于零知识证明的假名方案，以保护参与计算共享的用户隐私。最后，安全性分析和仿真结果表明，BECS能够充分有效地利用6G算力网络中的所有计算资源，在保护用户隐私的同时显著提高计算资源利用率。