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Article

An Efficient Resource Allocation Strategy for Edge-Computing Based Environmental Monitoring System

1
Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
2
Beijing Computing Center, Beijing 100094, China
3
National Computer Network Emergency Response Technical Team, Coordination Center of China, Beijing 100096, China
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(21), 6125; https://doi.org/10.3390/s20216125
Received: 30 September 2020 / Revised: 19 October 2020 / Accepted: 23 October 2020 / Published: 28 October 2020
(This article belongs to the Special Issue Internet of Things for Smart Homes II)
The cloud computing and microsensor technology has greatly changed environmental monitoring, but it is difficult for cloud-computing based monitoring system to meet the computation demand of smaller monitoring granularity and increasing monitoring applications. As a novel computing paradigm, edge computing deals with this problem by deploying resource on edge network. However, the particularity of environmental monitoring applications is ignored by most previous studies. In this paper, we proposed a resource allocation algorithm and a task scheduling strategy to reduce the average completion latency of environmental monitoring application, when considering the characteristic of environmental monitoring system and dependency among task. Simulations are conducted, and the results show that compared with the traditional algorithms. With considering the emergency task, the proposed methods decrease the average completion latency by 21.6% in the best scenario. View Full-Text
Keywords: environmental monitoring; edge computing; resource allocation; task scheduling environmental monitoring; edge computing; resource allocation; task scheduling
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MDPI and ACS Style

Fang, J.; Hu, J.; Wei, J.; Liu, T.; Wang, B. An Efficient Resource Allocation Strategy for Edge-Computing Based Environmental Monitoring System. Sensors 2020, 20, 6125. https://doi.org/10.3390/s20216125

AMA Style

Fang J, Hu J, Wei J, Liu T, Wang B. An Efficient Resource Allocation Strategy for Edge-Computing Based Environmental Monitoring System. Sensors. 2020; 20(21):6125. https://doi.org/10.3390/s20216125

Chicago/Turabian Style

Fang, Juan, Juntao Hu, Jianhua Wei, Tong Liu, and Bo Wang. 2020. "An Efficient Resource Allocation Strategy for Edge-Computing Based Environmental Monitoring System" Sensors 20, no. 21: 6125. https://doi.org/10.3390/s20216125

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