Leveraging Edge Computing Resource Orchestration to Improve QoS for IoT

Wen-Pin Lai, Yuhe Chang, Chien-Chang Liu, Wei-Cheng Lei, Li-Der Chou
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引用次数: 1

Abstract

Edge computing is to deploy micro data centers (MDCs) at the edge nodes of the network to provide services nearby, using the bandwidth of the edge network while reducing network delay. We propose the Greedy-based Resource Orchestration for IoT Edge Computing (GROTEC) mechanism that runs in edge computing environment. The GROTEC mechanism uses a global resource orchestrator to orchestrate the resources of the MDCs with a greedy strategy. The GROTEC mechanism includes a request dispatching algorithm, a request offloading mechanism and a service migration mechanism. The experiment results show that the request offloading mechanism of GROTEC reduces the duration of MDC being overloaded by 97.9%, decreases the network traffic of overloaded MDC by 91.9%, and improves the latency of requests by 12.6%. From the experiment results, the service migration mechanism of GROTEC can ease the load of the cloud data center and improve the latency of requests by 26.8%.
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利用边缘计算资源编排改善物联网的QoS
边缘计算是在网络的边缘节点上部署微型数据中心,就近提供服务,利用边缘网络的带宽,同时降低网络时延。我们提出了一种运行在边缘计算环境中的基于贪婪的物联网边缘计算资源编排(GROTEC)机制。GROTEC机制使用全局资源协调器以贪心策略对mdc的资源进行协调。GROTEC机制包括请求调度算法、请求卸载机制和服务迁移机制。实验结果表明,GROTEC的请求分流机制使MDC被过载的持续时间减少97.9%,使MDC过载的网络流量减少91.9%,使请求延迟减少12.6%。从实验结果来看,GROTEC的业务迁移机制可以缓解云数据中心的负载,并将请求延迟提高26.8%。
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