Minimum payment collaborative sensing network using mobile phones

Mobile phones with embedded sensors have been applied in various collaborative sensing applications. To encourage mobile phone users to perform collaborative sensing, the data demanders usually pay mobile phone users for required data. In this paper, we study the Minimum Payment of Attaining the Required Data with mobile phones (MPARD) problem in collaborative sensing network: given sensing regions \(R = \{R_1, R_2, \ldots , R_m\}\), the set of requisite data \(D_i\) for each sensing region \(R_i\) and a set of mobile phones \(M\), the \(MPARD\) problem studies how to select mobile phones to obtain all the required data such that the data demanders’ total payment to mobile phone users is minimized. In reality, some systems need the fresh sensing data from mobile phones at each pre-determined time slot, and others don’t require the real-time data and the sensing data from previous time slots is also deemed useful. Based on the above two different requirements of data timeliness, we first define two subproblems derived from \(MPARD\) problem: \(MPARD_t\) and \(MPARD_p\). After that, for each subproblem, we propose an approximation algorithm for the situation where the trajectories of mobile phones are determinate and a heuristic for the situation where trajectories are unknown. Simulation results demonstrate that our algorithms are efficient.