Cooperative Task Processing in Fog Computing Networks for Internet of Things
首发时间:2021-02-09
Abstract:Fog computing is a promising architecture to provide economic and low latency data services for Internet of things (IoT) network systems. In fog computing, multiple mobile devices (MDs) with redundant resources at the edge of the network, commonly referred to as the fog nodes, can be available to help the IoT MD to execute its tasks. In this paper, we design a fog computing framework to enable cooperative processing for delay-sensitive IoT tasks on resource-abundant fog nodes. Based on this framework, multiple fog nodes can cooperate in a fog group and simultaneously process the IoT tasks, so that the computational efficiency of fog networks can be further improved and the resources of fog nodes can be fully utilized. We formulate the cooperative task processing problem as a Winner Determination Problem (WDP) with the objective of maximizing the completion delay reduction of all IoT MDs and propose a cooperative greedy computing algorithm with a low complexity as our solution. Numerical studies confirm that the proposed scheme can obtain a better performance in task completion delay minimization compared with the reference schemes.
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物联网雾计算网络中的协同任务处理
摘要:雾计算是为物联网系统提供更经济和更低延迟数据服务的一种很有前途的体系结构。在雾计算中,在网络边缘具有冗余资源的多个移动设备(MD),通常被称为雾节点,可用于帮助物联网设备执行其任务。本文设计了一个雾计算框架,在资源丰富的雾节点上实现对时延敏感的物联网任务的协同处理。基于该框架,多个雾节点可以在一个雾节点组中协同工作,同时处理物联网任务,从而进一步提高网络的计算效率,充分利用雾节点的资源。我们将协同任务处理问题描述为一个赢家决定问题(WDP),目标是最大限度地减少所有物联网MD的完成延迟,并提出了一种低复杂度的协同贪婪计算算法作为我们的解决方案。数值研究表明,与参考方案相比,该方案在任务完成延迟最小化方面具有更好的性能。
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