arXiv subjects

Jiajun Sun

Publications and source records attributed to Jiajun Sun.

39 records · Page 3Linked to original sources

arXiv2014

Behavior-Based online Incentive Mechanism for Crowd Sensing with Budget Constraints

Crowd sensing is a new paradigm which leverages the ubiquity of sensor-equipped mobile devices to collect data. To achieve good quality for crowd sensing, incentive mechanisms are indispensable to attract more participants. Most of existing mechanisms focus on the expected utility prior to sensing, ignoring the risk of low quality solution and privacy leakage. Traditional incentive mechanisms such as the Vickrey-Clarke-Groves (VCG) mechanism and its variants are not applicable here. In this paper, to address these challenges, we propose a behavior based incentive mechanism for crowd sensing applications with budget constraints by applying sequential all-pay auctions in mobile social networks (MSNs), not only to consider the effects of extensive user participation, but also to maximize high quality of the context based sensing content submission for crowd sensing platform under the budget constraints, where users arrive in a sequential order. Through an extensive simulation, results indicate that incentive mechanisms in our proposed framework outperform the best existing solution.

cs.GT↗

arXiv2014

How Much Should I Pay for Privacy Concerns in Truthful Online Crowd Sensing?

Crowd sensing is a new paradigm which leverages the pervasive smartphones to efficiently collect sensing data, enabling numerous novel applications. To achieve good service quality for a crowd sensing application, incentive mechanisms are indispensable to attract more user participation. Most of existing mechanisms only apply for the offline scenario, where the system has full information about the users' sensing profiles, i.e., a set of locations or mobility as well as the type of smartphones used, and their true costs. On the contrary, we focus on a more real scenario where users with their own privacy concerns arrive one by one online in a random order. We model the problem as a privacy-respecting online auction in which users are willing to negotiate access to certain private information and submit their sensing profiles satisfying privacy concerns to the platform (the provider of crowd sensing applications) over time, and the platform aims to the total total value of the services provided by selected users under a budget constraint. We then design two online mechanisms for a budgeted crowd sensing application, satisfying the computational efficiency, individual rationality, budget feasibility, truthfulness, consumer sovereignty, constant competitiveness and privacy concerns. Through extensive simulations, we evaluate the performance and validate the theoretical properties of our online mechanisms.

cs.GT↗

arXiv2013

Uplink Scheduling Strategy Based on A Population Game in Vehicular Sensor Networks

Recent advances in the integration of vehicular sensor network (VSN) technology, and crowd sensing leveraging pervasive sensors called onboard units (OBUs), like smartphones and radio frequency IDentifications to provide sensing services, have attracted increasing attention from both industry and academy. Nowadays, existing vehicular sensing applications lack good mechanisms to improve the maximum achievable throughput and minimizing service time of participating sensing OBUs in vehicular sensor networks. To fill these gaps, in this paper, first, we introduce real imperfect link states to the calculation of Markov chains. Second, we incorporate the result of different link states for multiple types of vehicles with the calculations of uplink throughput and service time. Third, in order to accurately calculate the service time of an OBU, we introduce the steady state probability to calculate the exact time of a duration for back-off decrement, rather than using the traditional relative probability. Additionally, to our best knowledge, we first explore a multichannel scheduling strategy of uplink data access in a single roadside unit (RSU) by using a non-cooperative game in a RSU coverage region to maximize the uplink throughput and minimize service time under saturated and unsaturated traffic loads. To this end, we conduct a theoretical analysis and find the equilibrium point of the scheduling. The numerical results show that the solution of the equilibrium points are consistent with optimization problems.

cs.NI↗