Recent studies have shown that significant benefit can be achieved in wireless sensor networks (WSNs) by employing mobile collectors for data gathering via short-range communications. A typical scenario for such a scheme is that a mobile collector roams over the sensing field and pauses at some anchor points on its moving tour such that it can traverse the transmission range of all the sensors in the field and directly collect data from each sensor. In this paper, we study the performance optimization of such mobile data gathering by formulating it into a cost minimization problem constrained by channel capacity, required minimum data uploads from each sensor and bound of total sojourn time at all anchor points. In order to provide an efficient and distributed algorithm, we decompose this global optimization problem into two subproblems that can be solved by each sensor and the mobile collector, respectively. We show that such decomposition can be characterized as a pricing mechanism, in which each sensor independently adjusts its payment for the data uploading opportunity based on the shadow prices of different anchor points. Correspondingly, we give an efficient algorithm to jointly solve the two subproblems. Our theoretical analysis demonstrates that the proposed algorithm can achieve the optimal data control for each sensor and the optimal sojourn time allocation for the mobile collector, which minimizes the overall network cost. Finally, extensive simulation results further validate that our algorithm achieves lower cost than the compared data gathering strategy.
- convex problem
- Karush-Kuhn-Tucker (KKT) conditions
- Mobile data gathering
- pricing mechanism
ASJC Scopus subject areas
- Electrical and Electronic Engineering