移动边缘计算中计算卸载的延迟与吞吐量分析：一种排队网络方法
Delay and Throughput Analysis of Computation Offloading in Mobile Edge Computing: A Queueing Network Approach
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- Department of Electrical Engineering, Sharif University of Technology（电气工程系，谢里夫理工大学）
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中文总结 AI 辅助
本文提出乘积形式排队网络模型分析移动边缘计算中树形任务卸载的延迟，并通过可微优化框架设计静态卸载策略，数值验证其优于基线算法。
中文摘要 AI 辅助
移动边缘计算（MEC）使移动设备能够将计算任务卸载到附近的边缘服务器以及云端，以降低诸如增强现实/虚拟现实（AR/VR）、实时推理和传感器驱动分析等应用的端到端延迟。在本文中，我们研究了静态计算卸载问题，其中每个任务由多个相互依赖的子任务组成，这些子任务用一棵有根有向树表示。我们开发了一种乘积形式排队网络（PFQN）模型，并采用近似方法来捕捉多层MEC系统中树形结构任务执行的计算和通信动态。基于该模型，我们推导出了有效服务器利用率和等待时间的闭式表达式，然后构建了一种递归算法来评估一般树形结构任务的平均延迟。我们将静态卸载设计问题表述为在路由概率上最小化速率加权平均任务延迟，并通过基于softmax参数化、log-sum-exp平滑以及服务器利用率稳定性约束的可微优化框架来求解。数值结果表明，所提出的PFQN近似能够提供准确的延迟估计，且延迟优化的静态策略在平均任务延迟和经验最大稳定吞吐量方面均持续优于所考虑的基线算法。
英文摘要
Mobile edge computing (MEC) enables mobile devices to offload computation to nearby edge servers and to the cloud in order to reduce end-to-end delay for applications such as AR/VR, real-time inference, and sensor-driven analytics. In this paper, we study static computation offloading when each task consists of multiple dependent subtasks represented by a rooted directed tree. We develop a product-form queueing-network (PFQN) model with an approximation to capture the computation and communication dynamics of tree-structured task execution in a multi-tier MEC system. Based on this model, we derive closed-form expressions for effective server utilizations and waiting times, and then construct a recursive algorithm for evaluating the average delay of general tree-structured tasks. We formulate the static offloading design problem as the minimization of the rate-weighted average task delay over the routing probabilities, and solve it through a differentiable optimization framework based on softmax parameterization, log-sum-exp smoothing, and a stability barrier on server utilizations. Numerical results show that the proposed PFQN approximation provides accurate delay estimates and that the delay-optimized static policy consistently outperforms the considered baseline algorithms in terms of both average task delay and empirical maximum stable throughput.
