Computer Science ›› 2017, Vol. 44 ›› Issue (1): 113-116.doi: 10.11896/j.issn.1002-137X.2017.01.022

Previous Articles     Next Articles

Optimization Selection Mechanism for Service Nodes in Hybrid Crowd Sensing

HE Xin, LIU Tian-xu, DING Shuang and BAI Lin   

  • Online:2018-11-13 Published:2018-11-13

Abstract: The application of crowd sensing depends on the participation of mobile users.The sensing ability of the user is subject to their movement pattern,the remaining resources of the portable device,and other factors.Existing research work on service nodes selection is relatively simple,therefore it is necessary to design an optimization selection mechanism for selecting optimal service nodes set,ensuring the sensing quality of the target area.Based on the movement characteristics of the user,we proposed and defined the service metrics.Then,we designed the optimization selection mechanism using the genetic algorithm.The simulation results show that optimization selection mechanism can effectively select the best service nodes set,and then improve the service quality of the hybrid crowd sensing.

Key words: Crowd sensing,Optimal service nodes set,Optimization selection mechanism,Genetic algorithm

[1] GANTI R K,FAN Y,HUI L.Mobile crowdsensing:currentstate and future challenges[J].Communications Magazine,IEEE,2011,49(11):32-39.
[2] CHATZLMILIOUDIS G,KONSTANTINIDIS A,LAOUDIASC,et al.Crowdsourcing with smartphones [J].IEEE Internet Computing,2012,6(5):36-44.
[3] LIU Yun-hao.Crowdsourcing Computation[J].Communications of the CCF,2012,8(10):38-41.(in Chinese) 刘云浩.群智感知计算[J].中国计算机学会通讯,2012,8(10):38-41.
[4] HOWE J.The Rise of Crowdsourcing[J].Wired Magazine,2006,14(14):1-5.
[5] Campbell A T,Eisenman S B,Lane N D,et al.People-centric urban sensing[C]∥Proceedings of the 2nd Annual International Workshop on Wireless Internet.ACM,2006:18.
[6] CAMPBELL A T,et al.The Rise of People-Centric Sensing[J].Internet Computing,IEEE,2008,2(4):12-21.
[7] EISENMAN S B.People-centric mobile sensing networks[D].Columbia University,2008.
[8] CONTI M,GIORDANO S,MAY M,et al.From opportunisticnetworks to opportunistic computing[J].Communications Ma-gazine,IEEE,2010,48(9):126-139.
[9] AHMED A,YASUMOTO K,YAMUCHI Y,et al.Distance and time based node selection for probabilistic coverage in people-centric sensing[C]∥2011 8th Annual IEEE Communications Society Conference on Sensor,Mesh and Ad Hoc Communications and Networks (SECON).IEEE,2011:134-142.
[10] ZHAO D,MA H,LIU L.Energy-efficient opportunistic covera-ge for people-centric urban sensing[J].Wireless Networks,2014,20(6):1461-1476.
[11] SCELLATO S,et al.Next Place:A Spatio-Temporal Prediction Framework for Pervasive Systems[J].Lecture Notes in Computer Science,2011,6696(1):152-169.
[12] HSU W J,DUTTA D,HELMY A.CSI:A paradigm for beha-vior-oriented profile-cast services in mobile networks[J].Ad Hoc Networks,2012,10(8):1586-1602.
[13] DING S,HE X,WANG J,et al.Static Node Center Hexagonal Deployment in Hybrid Crowd Sensing[C]∥2015 IEEE 7th International Symposium on Cyberspace Safety and Security (CSS),2015 IEEE 12th International Conferen on Embedded Software and Systems (ICESS),2015 IEEE 17th International Conference on High Performance Computing and Communications (HPCC).IEEE,2015:515-520.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[2] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[3] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[4] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[5] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[6] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[7] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[8] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[9] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .
[10] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99, 116 .