Consider a multi-cell mobile edge computing network, in which each user wishes to compute the product of a user-generated data matrix with a network-stored matrix. This is done through task offloading by means of input uploading, distributed computing at edge nodes (ENs), and output downloading. Task offloading may suffer long delay since servers at some ENs may be straggling due to random computation time, and wireless channels may experience severe fading and interference. This paper aims to investigate the interplay among upload, computation, and download latencies during the offloading process in the high signal-to-noise ratio regime from an information-theoretic perspective. A policy based on cascaded coded computing and on coordinated and cooperative interference management in uplink and downlink is proposed and proved to be approximately optimal for a sufficiently large upload time. By investing more time in uplink transmission, the policy creates data redundancy at the ENs, which can reduce the computation time, by enabling the use of coded computing, as well as the download time via transmitter cooperation. Moreover, the policy allows computation time to be traded for download time. Numerical examples demonstrate that the proposed policy can improve over existing schemes by significantly reducing the end-to-end execution time.
翻译:考虑一个多细胞移动边缘计算网络,让每个用户都希望用一个网络存储矩阵来计算用户生成的数据矩阵的产物。这是通过输入上传、在边缘节点(ENs)上分布计算和下载输出下载的方式完成的任务卸载。任务卸载可能会受到长期拖延,因为某些ENs服务器可能由于随机计算时间而被拖累,无线频道可能经历严重减缩和干扰。本文的目的是从信息理论角度调查在高信号对噪音比率制度中卸载过程中的上传、计算和下载延迟之间的相互作用。基于级联编码计算以及上链接和下链接的协调和合作干扰管理的政策已经提出,并证明在足够大的上传时间里是最佳的。通过增加连接传输的时间,该政策在ENs造成数据冗余,这可以减少计算时间,通过使用编码计算,以及通过传输合作下载时间。此外,该政策允许在终端中计算时间,从而大大缩短了下载时间。Numericical 示例显示,通过执行现有政策可以大大改进。