TY - GEN
T1 - Maximizing data credibility under budget constraint for participatory sensing
AU - Gao, Hui
AU - Liu, Chi Harold
AU - Wang, Wendong
AU - Sheng, Zhengguo
AU - Chin, Alvin
AU - Tian, Ye
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/23
Y1 - 2015/11/23
N2 - Participatory sensing campaigns encourage ordinary people to collect and share sensing data by using their portable smart devices like smartphones, iPad and iWatch. However, compared with static sensors that are deployed in the particular places by people that can provide high-quality data, the quality of sensing data that are collected from smart devices is uncontrollable, and it is costly to pay data usage without knowing the credibility of the collected data. In this paper, we propose to leverage the participant's reputation to maximize total data credibility under budget constraint for participatory sensing systems. Specifically, we formally define a maximum sensing data credibility problem and present a trustable participants selection algorithm to obtain a near optimal solution. Provided the real data set, it has been shown by simulation results that our proposed algorithm selects more credible sensing data than that of the other two comparison algorithms.
AB - Participatory sensing campaigns encourage ordinary people to collect and share sensing data by using their portable smart devices like smartphones, iPad and iWatch. However, compared with static sensors that are deployed in the particular places by people that can provide high-quality data, the quality of sensing data that are collected from smart devices is uncontrollable, and it is costly to pay data usage without knowing the credibility of the collected data. In this paper, we propose to leverage the participant's reputation to maximize total data credibility under budget constraint for participatory sensing systems. Specifically, we formally define a maximum sensing data credibility problem and present a trustable participants selection algorithm to obtain a near optimal solution. Provided the real data set, it has been shown by simulation results that our proposed algorithm selects more credible sensing data than that of the other two comparison algorithms.
KW - Data credibility
KW - Participatory sensing
KW - Task budget
UR - http://www.scopus.com/inward/record.url?scp=84961705005&partnerID=8YFLogxK
U2 - 10.1109/HPCC-CSS-ICESS.2015.93
DO - 10.1109/HPCC-CSS-ICESS.2015.93
M3 - Conference contribution
AN - SCOPUS:84961705005
T3 - Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015
SP - 134
EP - 139
BT - Proceedings - 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security and 2015 IEEE 12th International Conference on Embedded Software and Systems, HPCC-CSS-ICESS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th IEEE International Conference on High Performance Computing and Communications, IEEE 7th International Symposium on Cyberspace Safety and Security and IEEE 12th International Conference on Embedded Software and Systems, HPCC-ICESS-CSS 2015
Y2 - 24 August 2015 through 26 August 2015
ER -