Social-Aware UAV-Assisted Mobile Crowd Sensing in Stochastic and Dynamic Environments for Disaster Relief Networks

被引：63

作者：

Wang, Bowen ^{[1
,2
]}

Sun, Yanjing ^{[1
]}

Liu, Dianxiong ^{[3
]}

Nguyen, Hien M. ^{[4
]}

Duong, Trung Q. ^{[2
]}

机构：

[1] China Univ Min & Technol, Sch Informat & Control Engn, Xuzhou 221116, Jiangsu, Peoples R China

[2] Queens Univ, Sch Elect Elect Engn & Comp Sci, Belfast BT7 1NN, Antrim, North Ireland

[3] Army Engineer Ing Univ, Coll Commun Engn, Nanjing 210007, North Ireland

[4] Duy Tan Univ, Danang 55000, Vietnam

来源：

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY | 2020年 / 69卷 / 01期

关键词：

Mobile crowd sensing; unmanned aerial vehicle; cyber-physical social system; task assignment; matching theory; ASSIGNMENT;

D O I：

10.1109/TVT.2019.2949634

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we consider a social-aware unmanned aerial vehicle (UAV) assisted mobile crowd sensing (MCS) system for disaster relief networks, and investigate how to recruit suitable UAVs to perform sensing tasks in stochastic and dynamic environments (both UAVs and tasks arrive stochastically). We formulate the task assignment problem into a dynamic matching problem, and propose a multiple-waitlist based task assignment (MWTA) algorithm to find the stable matching in time-varying environment. We prove that MWTA can achieve the dynamic stability containing the strategy-proofness, efficiency, and envy-freeness. Simulation results demonstrate the performance improvement of our proposed scheme compared with the traditional matching algorithm applied to deterministic matching model in stochastic setting.

引用

页码：1070 / 1074

页数：5

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