<listing id="l9bhj"><var id="l9bhj"></var></listing>
<var id="l9bhj"><strike id="l9bhj"></strike></var>
<menuitem id="l9bhj"></menuitem>
<cite id="l9bhj"><strike id="l9bhj"></strike></cite>
<cite id="l9bhj"><strike id="l9bhj"></strike></cite>
<var id="l9bhj"></var><cite id="l9bhj"><video id="l9bhj"></video></cite>
<menuitem id="l9bhj"></menuitem>
<cite id="l9bhj"><strike id="l9bhj"><listing id="l9bhj"></listing></strike></cite><cite id="l9bhj"><span id="l9bhj"><menuitem id="l9bhj"></menuitem></span></cite>
<var id="l9bhj"></var>
<var id="l9bhj"></var>
<var id="l9bhj"></var>
<var id="l9bhj"><strike id="l9bhj"></strike></var>
<ins id="l9bhj"><span id="l9bhj"></span></ins>
Volume 39 Issue 12
Dec.  2017
Turn off MathJax
Article Contents
YANG Jing, LI Peng-cheng, YAN Jun-jie. MCS data collection mechanism for participants' reputation awareness[J]. Chinese Journal of Engineering, 2017, 39(12): 1922-1934. doi: 10.13374/j.issn2095-9389.2017.12.020
Citation: YANG Jing, LI Peng-cheng, YAN Jun-jie. MCS data collection mechanism for participants' reputation awareness[J]. Chinese Journal of Engineering, 2017, 39(12): 1922-1934. doi: 10.13374/j.issn2095-9389.2017.12.020

MCS data collection mechanism for participants' reputation awareness

doi: 10.13374/j.issn2095-9389.2017.12.020
  • Received Date: 2017-01-15
  • Task participants' malicious behavior can significantly reduce the credibility of mobile crowd sensing (MCS). To solve this problem, this paper proposed a data collection mechanism that analyzed and quantified participants' historical reputation according to their willingness and the quality of data they had shared, and then updated their current reputation through the logistic regression model. Simultaneously, to measure the authenticity of the collected data, the participants were divided into two types:those who were related to direct transmission of sensing data and second, those who were involved in indirect forwarding of these, which was based on the remaining transmission time of sensing data and residual energy of mobile equipment. Then the server analyzed the accuracy of data collected by participants according to the multitasking scenario. Simulation results show that the proposed mechanism can significantly improve the perceived tasks performed in real time, greatly upgrade the quality of sensing data, and effectively reduce the reward expenses.

     

  • loading
  • [1]
    Yürür Ö, Liu C H, Sheng Z G, et al. Context-awareness for mobile sensing:a survey and future directions. IEEE Commun Surv Tut, 2016, 18(1):68
    [2]
    Wang L Y, Zhang D Q, Yan Z X, et al. effSense:a novel mobile crowd-sensing framework for energy-efficient and cost-effective data uploading. IEEE T Syst Man Cy, 2015, 45(12):1549
    [3]
    Bazzi A, Zanella A. Position based routing in crowd sensing vehicular networks. Ad Hoc Netw, 2016, 32:409
    [4]
    Liu L, Wei W Y, Zhao D, et al. Urban resolution:new metric for measuring the quality of urban sensing. IEEE T Mobile Comput, 2015, 14(12):2560
    [5]
    Guo B, Chen H H, Yu Z W, et al. FlierMeet:a mobile crowdsensing system for cross-space public information reposting, tagging, and sharing. IEEE T Mobile Comput, 2015, 14(10):2020
    [6]
    Guo B, Yu Z W, Chen L M, et al. MobiGroup:enabling lifecycle support to social activity organization and suggestion with mobile crowd sensing. IEEE T Hum-Mach Syst, 2016, 46(3):390
    [7]
    Wu D P, He J, Wang H G, et al. A hierarchical packet forwarding mechanism for energy harvesting wireless sensor networks. IEEE Commun Mag, 2015, 53(8):92
    [8]
    Wang K, Qi X, Shu L, et al. Toward trustworthy crowdsourcing in the social internet of things. IEEE Wirel Commun, 2016, 23(5):30
    [9]
    Yang D J, Xue G L, Fang X, et al. Incentive mechanisms for crowd sensing:crowdsourcing with smartphones. IEEE ACM T Network, 2016, 24(3):1732
    [10]
    Zhao D, Li X Y, Ma H D. Budget-Feasible online incentive mechanisms for crowdsourcing tasks truthfully. IEEE ACM T Network, 2016, 24(2):647
    [11]
    Di B Y, Wang T Y, Song L Y, et al. Collaborative smartphone sensing using overlapping coalition formation games. IEEE T Mobile Comput, 2017, 16(1):30
    [12]
    Gisdakis S, Giannetsos T, Papadimitratos P. Security, privacy, and incentive provision for mobile crowd sensing systems. IEEE Internet Things, 2016, 3(5):839
    [13]
    Sun J J, Ma H D. Heterogeneous-belief based incentive schemes for crowd sensing in mobile social networks. J Netw Comput Appl, 2014, 42:189
    [14]
    Shah-Mansouri H, Wong V W S. Profit maximization in mobile crowdsourcing:a truthful auction mechanism//IEEE International Conference on Communications (ICC). London, 2015:3216
    [15]
    Wen Y T, Shi J Y, Zhang Q, et al. Quality-driven auctionbased incentive mechanism for mobile crowd sensing. IEEE T Veh Technol, 2015, 64(9):4203
    [16]
    Krontiris I, Albers A. Monetary incentives in participatory sensing using multi-attributive auctions. Int J Parallel, Emergent Distributed Syst, 2012, 27(4):317
    [17]
    Liu C H, Zhang B, Su X, et al. Energy-aware participant selection for smartphone-enabled mobile crowd sensing. IEEE Syst J, 2017, 11(3):1435
    [18]
    Su F, Dong H H, Jia L M, et al. On urban road traffic state evaluation index system and method. Mod Phys Lett B, 2017, 31(1):1650428
    [19]
    Bhunia S S, Pal J, Mukherjee N. Fuzzy assisted event driven data collection from sensor nodes in sensor-cloud infrastructure//14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid). Chicago, 2014:635
    [21]
    Zhang Z H. Variable selection with stepwise and best subset approaches. Ann Transl Med, 2016, 4(7):136
    [22]
    Obrechkoff N. On the summation of Taylor's series on the contour of the domain of summability. Fract Calc Appl Anal, 2016, 19(5):1316
    [23]
    Wang L, Shi Y M, Yan W A. Inference for Gompertz distribution under records. J Syst Eng Electron, 2016, 27(1):271
    [24]
    Goh S K, Abbass H A, Tan K C, et al. Decompositional independent component analysis using multi-objective optimization. Soft Comput, 2016, 20(4):1289
    [25]
    Aberer K. Keynote:OpenSense:open sensor networks for air quality monitoring//IEEE International Conference on Pervasive Computing & Communications Workshops (PERCOM Workshops). Lugano, 2012:1
  • 加載中

Catalog

    通訊作者: 陳斌, bchen63@163.com
    • 1. 

      沈陽化工大學材料科學與工程學院 沈陽 110142

    1. 本站搜索
    2. 百度學術搜索
    3. 萬方數據庫搜索
    4. CNKI搜索
    Article views (631) PDF downloads(15) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return
    久色视频