基于公交网络的车载群智感知方法及其优化
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摘要
公交车具有固定的行驶路线和发车周期、统一的车载设备标准、低隐私泄露风险等特性。根据公交车的特性,设计了一个基于公交网络的车载群智感知系统,系统中的数据中心通过公交网络中的公交车来采集城市数据,以满足数据用户的需求;随后研究系统中的任务分配问题和数据交易问题。基于贪婪算法设计优化任务分配策略以最小化系统的数据采集能耗成本,并根据博弈论设计最优数据交易策略以最大化系统的经济效益。最后通过仿真,验证了提出的策略的有效性和优越性。
Public buses have unique characteristics,such as fixed moving paths and time periods,uniform vehicular device standards,low risk of privacy exposure. This paper designed a public bus network-based vehicular crowd sensing system,considering the characteristics of public buses. In the system,data center utilized public buses of the bus network to collect urban data which was required by data users. It also studied the task assignment problem and the data trading problem in the system.This paper proposed an optimized task assignment strategy based on a greedy algorithm to minimize the system energy consumption of data collection,and proposed an optimal data trading strategy based on game theory to maximize the system utility. Finally,numerical results demonstrate the effectiveness of proposed strategies.
Public buses have unique characteristics,such as fixed moving paths and time periods,uniform vehicular device standards,low risk of privacy exposure. This paper designed a public bus network-based vehicular crowd sensing system,considering the characteristics of public buses. In the system,data center utilized public buses of the bus network to collect urban data which was required by data users. It also studied the task assignment problem and the data trading problem in the system.This paper proposed an optimized task assignment strategy based on a greedy algorithm to minimize the system energy consumption of data collection,and proposed an optimal data trading strategy based on game theory to maximize the system utility. Finally,numerical results demonstrate the effectiveness of proposed strategies.
引文
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[3]Ganti R K,Ye Fan,Lei H.Mobile crowd sensing:current state and future challenges[J].IEEE Communications Magazine,2011,49(11):32-39.
[4]Chen Yin,Nakazawa J,Yonezawa T,et al.An empirical study on coverage-ensured automotive sensing using door-to-door garbage collecting trucks[C]//Proc of the 2nd International Workshop on Smart.New York:ACM Press,2016:article No.6.
[5]Lee U,Magistretti E,Gerla M,et al.Dissemination and harvesting of urban data using vehicular sensing platforms[J].IEEE Trans on Vehicular Technology,2009,58(2):882-901.
[6]Liu Yazhi,Niu Jianwei,Liu Xiting.Comprehensive tempo-spatial data collection in crowd sensing using a heterogeneous sensing vehicle selection method[J].Personal and Ubiquitous Computing,2016,20(3):397-411.
[7]Liu Yazhi,Wang Wendong,Ma Yuekun,et al.Distributed task offloading in heterogeneous vehicular crowd sensing[J].Sensors,2016,16(7):1090.
[8]Lee U,Gerla M.A survey of urban vehicular sensing platforms[J].Computer Networks,2010,54(4):527-544.
[9]Liu Yazhi,Li Xiong.Heterogeneous participant recruitment for comprehensive vehicle sensing[J].PLo S ONE,2015,10(9):e0138898.
[10]Jia Jie,Chen Jian,Chang Guiran,et al.Multi-objective optimization for coverage control in wireless sensor network with adjustable sensing radius[J].Computers&Mathematics with Applications,2009,57(11):1767-1775.
[11]Huang Shiwei,Chen Hongbin,Zhang Yan,et al.Sensing-energy tradeoff in cognitive radio networks with relays[J].IEEE Systems Journal,2013,7(1):68-76.
[12]田烽楠,王于.求解0-1背包问题算法综述[J].软件导刊,2009,8(1):59-61.(Tian Fengnan,Wang Yu.Overview of algorithms for solving 0-1 knapsack problem[J].Software Guide,2009,8(1):59-61.)
[13]Maharjan S,Zhu Quanyan,Zhang Yan,et al.Dependable demand response management in the smart grid:a Stackelberg game approach[J].IEEE Trans on Smart Grid,2013,4(1):120-132.
[14]Tushar W,Chai B,Yuen C,et al.Three-party energy management with distributed energy resources in smart grid[J].IEEE Trans on Industrial Electronics,2015,62(4):2487-2498.
[15]Zhu J Y,Sun Chenxi,Li V O K.Granger-causality-based air quality estimation with spatio-temporal(ST)heterogeneous big data[C]//Proc of IEEE Conference on Computer Communications Workshops.Piscataway,NJ:IEEE Press,2015:612-617.
[16]Jetcheva J G,Hu Y C,Pal Chaudhuri S,et al.CRAWDAD dataset rice/ad_hoc_city[DB/OL](2003-09-11).http://crawdad.org/rice/ad_hoc_city/20030911.