下一代边缘计算:实现净零排放的路线图

Raghubir Singh , Sukhpal Singh Gill
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摘要

多接入边缘计算(MEC,前身为移动边缘计算)通过将计算任务卸载到地理位置接近的优势计算资源上,为智能手机等移动设备(MD)的用户提供了计算任务完成时间上的优势。作为实现净零排放的第一步,有必要使这些服务更具可持续性(高能效)。我们将零延迟边缘节点-MD 连接模拟为与专用服务器相连的单个基站,MD 通过无线局域网 (WLAN) 发送和接收数据,并尽可能使用可识别的实际额定功率。在本文中,我们证明了在 3 G、4 G 和 5 G WLAN 网络中,MD 和边缘节点硬件的总能耗明显低于 MD 本身的能耗。节能效果(以 MD 单独使用的能源百分比计算)与数据文件大小无关,在计算任务更复杂、MD CPU 工作负载较高但服务器 CPU 工作负载适中的情况下,节能效果更大。节能效果在很大程度上取决于基站与服务器类型的精确配置(峰值额定功率、CPU 内核数和同时处理的最大作业数)。5 G 基站的功耗最高,但这被更快的 WLAN 速度所抵消,与单独的 MD 计算相比,可节省超过 90% 的能源。我们讨论了这些结果对减少全球用电量和实现碳中和以实现净零排放的意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Next generation edge computing: A roadmap to net zero emissions

Multi-access Edge Computing (MEC, formerly, Mobile Edge Computing) offers users of Mobile Devices (MDs) such as smartphones advantages in computational task completion times by offloading to superior but geographically close computing resources. There is a need to make these services more sustainable (energy-efficient) as an initial step towards net zero emissions. We have modelled a zero-latency edge node-MD connection as a single base station linked to a devoted server with the MD transmitting and receiving data via a Wireless Local Area Network (WLAN) with, wherever possible, identifiable real-world power ratings. In this paper, we demonstrate that the total energy usage by the MD and edge node hardware can be markedly less than that of the MD alone in 3 G, 4 G and 5 G WLAN networks. The energy savings, computed as percentages of MD-alone energy usage, are independent of data file size, are greater with computationally more complex tasks, and have a higher MD CPU workload but moderate server CPU workloads. Energy savings are highly dependent on the precise configuration of the base station with server type (peak power rating, the number of CPU cores and the maximum number of jobs processed simultaneously). A 5 G base station has the highest power consumption, but this is offset by much faster WLAN speeds, which can result in energy savings in excess of 90% compared with MD computation alone. We discuss the implications of these results for reducing global electricity use and achieving carbon neutrality to contribute towards net zero emissions.

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