Edge-Cloud Collaborative Worker Recruitment Algorithm in Mobile Crowd Sensing System

被引：0
作者：
Xi H. [1 ,2 ]
Zhu J. [2 ]
Li J. [3 ]
机构：
[1] School of Electronic Engineering, Heilongjiang University, Harbin
[2] School of Computer Science and Technology, Heilongjiang University, Harbin
[3] Shandong Artificial Intelligence Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan
来源：
Beijing Youdian Daxue Xuebao/Journal of Beijing University of Posts and Telecommunications | 2022年 / 45卷 / 04期
关键词：
Edge-cloud collaboration; Mobile crowd sensing; Spatial coverage; Worker recruitment;
D O I：
10.13190/j.jbupt.2021-205
中图分类号：
学科分类号：
摘要：
Since the recruitment algorithms based on cloud platform cannot meet the needs of large scale network real-time tasks, an edge-cloud collaboration recruitment algorithm is proposed whose aim is to reduce the data transmission delay and the energy consumption of intelligent devices. The cloud service layer performs task reception, division, release and result collection; the edge layer performs obtaining the real-time information of workers and constructing the recruitment model of workers, while the perceptual layer performs task propagation and data collection. The experimental results show that the proposed algorithm can not only meet the cost and time constraints, but also achieve good performance in space coverage and time by taking consideration of sensor type, worker quotation and the maximum number. © 2022, Editorial Department of Journal of Beijing University of Posts and Telecommunications. All right reserved.
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页码：77 / 83
页数：6
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