Research Of Incentive Mechanism Based On Information Quality In Participatory Sensing Systems

The rapid development of the Internet and wireless communication technologies,leading us into the mobile Internet age.Smart phone as a representative of the intelligent wireless terminal equipment has changed our life styles.We can collect and share information by using smart phone anywhere,any place,anytime.Participatory sensing make use of mobile Internet,cloud computing and big data to form a closed loop,and help people to perform data collection,data analysis,data sharing.Ultimately,people can get valuable information in participatory sensing environment and help making decision.Participatory sensing system is people-centric system that heavily depend on user's participation and coverage.But collect sensing data need to consume energy,time,money and computing power,these factors hinder participants to perform sensing task.Incentive mechanism could attracts more users to participate and improve participation level.In order to incentive the users of the participatory sensing systems to perform sensing task actively,increase the number of sensing task and improve user participation level,we proposed Dynamic Price Incentive Mechanism Based Data Quality,DPIM,which according to the data quality of sensing information which uploaded by users to determine the reward of participant.The results of simulation show that the DPIM algorithm not only enhances participant's participation and increases the number of sensing task,while motivating participants to provide high-quality sensing data.To reduce the payment cost of the consumer who gets sensing data from participants,we propose Sensing Task Classification Algorithm base on DPIM incentive mechanism,STCA.Participatory sensing systems will separate all location of interest into two sets according to average sensing frequency in each sensing time slice.When the sensing frequency at a LoI lower than the average sensing frequency,consumer could cost less payment,and to help consumer reduces payment.The simulation show that compare to DPIM,STCA reduce average payment cost of consumers,not only enhances participant participation and increase the number of sensing task,while motivating participants to provide high-quality sensing data.Finally,the existing problems in malicious participants and low sensing data for participatory sensing system,we propose History based Reputation Algorithm,HRA.The HRA uses direct reputation and indirect reputation to compute overall reputation of the users.The participatory sensing systems will reduce to push sensing task to participants with low reputation score,and decrease transactions risk for consumers.The simulation results show that the HRA algorithm improves data quality in the participatory sensing systems,while resisting attacks of malicious participants and keeping security and reliability.