Efficient Data Gathering with Mobile Collectors and Space-Division Multiple Access Technique in Wireless Sensor Networks

Abstract

Recent years have witnessed a surge of interest in efficient data gathering schemes in wireless sensor networks (WSNs). In this paper, we address this issue by adopting mobility and space-division multiple access (SDMA) technique. Specifically, mobile collectors, called SenCars in this paper, work like mobile base stations and collect data from associated sensors via single-hop transmissions so as to achieve uniform energy consumption. We also apply SDMA technique to data gathering by equipping each SenCar with multiple antennas such that distinct compatible sensors may successfully make concurrent data uploading to a SenCar. To investigate the utility of the joint design of controlled mobility and SDMA technique, we consider two cases, where a single SenCar and multiple SenCars are deployed in a WSN, respectively. For the single SenCar case, we aim to minimize the total data gathering time, which consists of the moving time of the SenCar and the data uploading time of sensors, by exploring the trade-off between the shortest moving tour and the full utilization of SDMA. We refer to this problem as mobile data gathering with SDMA, or MDG-SDMA for short. We formalize it into an integer linear program (ILP) and propose three heuristic algorithms for it. In the multi-SenCar case, the sensing field is divided into several regions, each having a SenCar. We focus on minimizing the maximum data gathering time among different regions and refer to it as mobile data gathering with multiple SenCars and SDMA (MDG-MS) problem. Accordingly, we propose a region-division and tour-planning (RDTP) algorithm in which data gathering time is balanced among different regions. We carry out extensive simulations and the results demonstrate that our proposed algorithms significantly outperform single SenCar and non-SDMA schemes.