Beaconing Control strategy based on Game Theory in mobile crowdsensing

Mobile crowdsensing is a new paradigm in which a group of mobile users exploit their smart devices to cooperatively perform a large-scale sensing job over urban environments. According to the different price plans, all the users could be segmented into following two groups: Pay as you go (PAYG) and Pay monthly (PAYM). Taking the uploading cost into consideration, a PAYG user prefers to upload the sensing data through a PAYM user, rather than uploading it by itself. In order to utilize the limited energy to deliver the sensing data to the PAYM users, each user should decide a suitable switch between high beaconing frequency and low beaconing frequency. In this paper, we propose a Beaconing Control strategy based on the Game Theory in mobile crowdsensing (BCGT), where each user decides the beaconing frequency according to its payoffs between sensing data delivery ratio and energy consumption. Then, each user's life cycle is divided into three phases: high beaconing phase, game theory phase, and low beaconing phase, in order to efficiently utilize the limited energy. We conduct extensive simulations based on random-waypoint mobility pattern and two widely-used real-world traces: roma/taxi and epfl. The results show that compared with other beaconing control strategies, BCGT achieves a higher delivery ratio with an identical initial energy.