Multi-access Edge Computing (MEC) enables computation and energy-constrained devices to offload and execute their tasks on powerful servers. Due to the scarce nature of the spectral and computation resources, it is important to jointly consider i) contention-based communications for task offloading and ii) parallel computing and occupation of failure-prone MEC processing resources (virtual machines). The feasibility of task offloading and successful task execution with virtually no failures during the operation time needs to be investigated collectively from a combined point of view. To this end, this letter proposes a novel spatiotemporal framework that utilizes stochastic geometry and continuous time Markov chains to jointly characterize the communication and computation performance of dependable MEC-enabled wireless systems. Based on the designed framework, we evaluate the influence of various system parameters on different dependability metrics such as (i) computation resources availability, (ii) task execution retainability, and (iii) task execution capacity. Our findings showcase that there exists an optimal number of virtual machines for parallel computing at the MEC server to maximize the task execution capacity.

中文翻译：

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启用 MEC 的无线系统中的时空可靠任务执行服务

多访问边缘计算 (MEC) 使计算和能源受限的设备能够在功能强大的服务器上卸载和执行其任务。由于频谱和计算资源的稀缺性，重要的是要共同考虑 i) 用于任务卸载的基于争用的通信和 ii) 并行计算和易发生故障的 MEC 处理资源（虚拟机）的占用。需要从组合的角度共同研究任务卸载和成功执行任务的可行性，并且在操作期间几乎没有故障。为此，这封信提出了一种新颖的时空框架，该框架利用随机几何和连续时间马尔可夫链来共同表征支持 MEC 的可靠无线系统的通信和计算性能。基于设计的框架，我们评估了各种系统参数对不同可靠性指标的影响，例如（i）计算资源可用性、（ii）任务执行可保留性和（iii）任务执行能力。我们的研究结果表明，MEC 服务器上存在用于并行计算的最佳虚拟机数量，以最大限度地提高任务执行能力。