GPU-specific Task Offloading in the Mobile Edge Computing Network

Namkyu Kim, Yunseong Lee, Chunghyun Lee, The-Vi Nguyen, Van Dat Tuong, Sungrae Cho
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引用次数: 4

Abstract

Graphics processing unit (GPU)-specific tasks can be done by mobile edge computing in 5G networks because user equipments (UEs) offload the tasks near to Edge Server such as smart phones, access points, and so on. The data produced by Internet of Things devices can not be managed by traditional cloud computing system because of limited resource. Edge Computing is promising solution to this problem. The edge computing server is placed at the edge of network near the UEs. As a result, edge computing system guarantees low latency and energy-efficient task processing of the UEs. This paper introduces the system model for GPU-specific Task Offloading in the Mobile Edge Computing Networks and discusses the solutions for this problem.
移动边缘计算网络中特定gpu的任务卸载
特定于图形处理单元(GPU)的任务可以通过5G网络中的移动边缘计算完成,因为用户设备(ue)会卸载边缘服务器附近的任务,如智能手机、接入点等。由于资源有限,传统的云计算系统无法对物联网设备产生的数据进行管理。边缘计算很有希望解决这个问题。边缘计算服务器位于网络的边缘,靠近终端。因此,边缘计算系统可以保证终端的低延迟和高能效的任务处理。本文介绍了移动边缘计算网络中gpu特定任务卸载的系统模型,并讨论了该问题的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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