The National Natural Science Foundation of China(62071179);The National Key Research and Development Program of China(2022-YFB-2503202);Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing
随着6G通信网络和移动边缘计算(mobile edge computing,MEC)技术的迅速发展,配备边缘服务器的基站部署密度持续提高,计算任务呈现出日益多样化的趋势。为应对差异化用户体验质量(quality of experience,QoE)以及资源分配不均衡对系统性能的影响,提出了一种高效的匹配卸载方案,综合考虑了卸载决策以及计算资源分配,构建了一个以最大化系统收益为目标的混合整数非线性规划问题。通过分解原问题,基于双边匹配理论设计了一种迭代优化算法加以求解。仿真实验基于澳大利亚墨尔本中央商务区(central business district,CBD)的公共数据集进行验证,结果表明,与现有方案相比,所提方案在提升系统收益方面表现出显著的优势。
Abstract
With the rapid development of 6G communication networks and mobile edge computing(MEC) technology
the deployment density of base stations equipped with edge servers has been continuously increasing
and computational tasks show a growing trend toward diversification. To address the impact of differentiated quality of experience (QoE) for users and unbalanced resource allocation on system performance
an efficient matching offloading scheme was proposed. The scheme comprehensively considered both offloading decisions and computational resource allocation
and a mixed-integer nonlinear programming problem was formulated with the objective of maximizing system utility. By decomposing the original problem
an iterative optimization algorithm was designed based on bilateral matching theory for solution. Simulation experiments were conducted using public datasets from the central business district (CBD) of Melbourne
Australia. The results demonstrate that
compared with existing schemes
the proposed scheme shows significant advantages in improving system utility.
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references
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