计算机科学 ›› 2018, Vol. 45 ›› Issue (11): 304-311.doi: 10.11896/j.issn.1002-137X.2018.11.049
黄志清1,2, 李梦佳1,2, 田锐1,2, 张严心3, 王伟东1,2
HUANG Zhi-qing1,2, LI Meng-jia1,2, TIAN Rui1,2, ZHANG Yan-xin3, WANG Wei-dong1,2
摘要: 车联网能高效地实现感知区域的覆盖,因此被应用于大规模城市感知。同时,为了解决车联网难以传输大量数据的问题,一些研究者使用压缩感知对具有时空相关性的数据进行压缩。但是,目前在车联网中应用压缩感知的研究并没有考虑数据和车辆分布变化的特性,很可能导致不可接受的误差。为了保证数据的重构精度,提出面向车联网的动态压缩感知方法。该方法能自动分析感知对象的数据特征、车辆分布和观测数量之间的关系。在压缩感知的基础上加入观测数量调整功能,通过对当前感知对象的数据特征和车辆分布的分析,实时调整压缩感知中观测矩阵的参数,从而控制观测数据的数量,提升重构精度,实现更高质量的数据传输。实验表明与现有车联网中的压缩感知方法相比,面向车联网的动态压缩感知方法在重构精度上提升了15.3%。
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[1]NEIROTTIP,MARCOA D,CAGLIANOA C,et al.Current trends in Smart City initiatives:Some stylised facts[J].Cities,2014,38(5):25-36. [2]LIU J,LI Y,CHEN M,et al.Software-defined internet of things for smart urban sensing[J].Communications Magazine IEEE,2015,53(9):55-63. [3]JALALVANDIS,RAFEHR.A cluster-based routing algorithm for VANET[C]∥IEEE International Conference on Computer and Communications.IEEE,2016:2068-2072. [4]LIU K,NG J K Y,LEE V C S,et al.Cooperative data scheduling in hybrid vehicular ad hoc networks:VANET as a software defined network[J].IEEE/ACM Transactions on Networking,2016,24(3):1759-1773. [5]HE J,CAI L,CHENG P,et al.Delay Minimization for Data Dissemination in Large-scale VANETs with Buses and Taxis[J].IEEE Transactions on Mobile Computing,2016,15(8):1939-1950. [6]LEE U,MAGISTRETTI E,GERLA M,et al.Dissemination and Harvesting of Urban Data using Vehicular Sensor Platforms[J].IEEE Transactions on Vehicular Technology,2009,58(2):882-901. [7]SALHI I,CHERIF M O,SENOUCI S M.A New Architecture for Data Collection in Vehicular Networks[C]∥IEEE International Conference on Communications.IEEE Press,2009:2705-2710. [8]JANG J,YANG Y,SMYTH A W,et al.Framework of Data Acquisition and Integration for the Detection of Pavement Distress via Multiple Vehicles[J].Journal of Computing in Civil Engineering,2016,31(2):04016052. [9]MALIK A,PANDEY B.An Intelligent Authentication Based Vehicle Initiated Broadcast-Dynamic Path Data Collection Scheme in VANET[J].Indian Journal of Science & Technology,2016,9(16):1-9. [10]ANASTASI G,ANTONELLI M,BECHINI A,et al.Urban and social sensing for sustainable mobility in smart cities[C]∥Sustainable Internet and ICT for Sustainability.IEEE,2013:1-4. [11]ZHU Y,LIU X,WANG Y.Pervasive Urban Sensing with Large-Scale Mobile Probe Vehicles[J].International Journal of Distributed Sensor Networks,2013,2013:177-182. [12]HULL B,BYCHKOVSKY V,ZHANG Y,et al.CarTel:a distributed mobile sensor computing system[C]∥International Conferece on Embedded Networked Sensor Systems.2006:125-138. [13]HU S C,WANG Y C,HUANG C Y,et al.A vehicular wireless sensor network for CO2 monitoring[C]∥Sensors,2009 IEEE.2009:1498-1501. [14]DONOHO D L.Compressive sensing[J].IEEE Transactions on Information Theory,2006,52(4):1289-1306. [15]YU X,ZHAO H,ZHANG L,et al.Cooperative Sensing and Compression in Vehicular Sensor Networks for data gathering[C]∥IEEE International Conference on Communications.IEEE Xplore,2010:1-5. [16]WANG H,ZHU Y,ZHANG Q.Compressive sensing based monitoring with vehicular networks[C]∥IEEE INFOCOM.IEEE,2013:2823-2831. [17]LIU C,CHIGAN C,GAO C.Compressive sensing based data collection in VANETs[C]∥Wireless Communications and NETWORKING Conference.IEEE,2013:1756-1761. [18]ZHU Y,LI Z,ZHU H,et al.A Compressive Sensing Approach to Urban Traffic Estimation with Probe Vehicles[J].IEEE Transactions on Mobile Computing,2013,12(11):2289-2302. [19]WANG G Y,JIANG Y J,MO L F,et al.Dynamic measurement policy for soil respiraten monitoring sensor networks based on compressive sensing[J].Scientia Sinica,2013,43(10):1326-1341.(in Chinese) 王国英,江雨佳,莫路锋,等.基于压缩感知的土壤呼吸监测传感网动态采样调度策略[J].中国科学:信息科学,2013,43(10):1326-1341. [20]QUER G,ZORDAN D,MASIERO R,et al.WSN-Control:Signal reconstruction through Compressive Sensing in Wireless Sensor Networks[C]∥The IEEE Conference on Local ComputerNetworks.2010:921-928. [21]HAO J,ZHANG B,JIAO Z,et al.Adaptive compressive sensing based sample scheduling mechanism for wireless sensor networks[J].Pervasive & Mobile Computing,2015,22(C):113-125. [22]RADOVIC' M,DUKNIC' M,TASESKI J.Sensing,Compression,and reconstruction for WSNs:Sparse Signal Modeling and Monitoring Framework [J].IEEE Transactions on Wireless Communications,2012,11(10):3447-3461. [23]WANG J,TANG S,YIN B,et al.Data gathering in wireless sensor networks through intelligent compressive sensing[J].IEEE INFOCOM,2012,131(5):603-611. [24]CHEN W,WASSELL I J.Energy efficient signal acquisition via compressive sensing in wireless sensor networks[C]∥2011 6th International Symposium on Wireless and Pervasive Computing (ISWPC).IEEE,2011:1-6. [25]FRAGKIADAKIS A,CHARALAMPIDIS P,TRAGOS E. Adaptive compressive sensing for energy efficient smart objects in IoT applications[C]∥International Conference on Wireless Communications.2014:1-5. [26]CANES E,ROMBERG J.Sparsity and incoherence in compressive sampling[J].Inverse Problems,2006,23(3):969-985. [27]HECHT-NIELSEN R.Theory of backpropagation neural net- works[C]∥International Joint Conference on Neural Networks.IEEE Xplore,1989:593-605. [28]LI B,LIU C.Parallel BP Neural Network on Single-chip Cloud Computer[C]∥IEEE International Conference on High Performance Computing and Communications.IEEE,2015:1871-1875. [29]TROPPJ A,GILBEFTA C.Signal reconstruction From Random Measurements Via Orthogonal Matching Pursuit[J].IEEE Transactions on Information Theory,2008,53(12):4655-4666. [30]GRIGGSW M,ORDÓÑEZ-HURTADO R H,CRISOSTOMI E,et al.A Large-Scale SUMO-Based Emulation Platform[J].IEEE Transactions on Intelligent Transportation Systems,2015,16(6):3050-3059. |
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