Many-to-Many Data Collection for Mobile Users in Wireless Sensor Networks

Abstract

Data collection is one of the fundamental functions in Wireless Sensor Networks (WSNs). Different from traditional data collection mechanisms which only consider a single and stationary sink, this paper studies this problem in a scenario with multiple mobile sinks. The motivation is for a WSN to support future applications, such as Internet of Things (IoT). In this case, a WSN is required to be able to deliver sensing results to multiple users moving around the network. There are two difficulties in this problem: sink mobility and multiple sinks. Since sinks are mobile, data delivery paths need to be updated frequently, which causes huge maintenance cost. To resolve this problem, we propose a hop-count based data collection architecture together with an efficient mobility management scheme. On the other side, sensing results from a large number of sensors are sent to multiple sinks, which causes lots of packet transmissions. To resolve this problem, we combine the idea of multicast and data aggregation. We first prove that the optimal multicast decision is a NP-hard problem and then propose a distributed heuristic solution. In addition, we further integrate data aggregation into multicast and propose a distributed many-to-many aggregation mechanism. Simulations are constructed to show the efficiency of the proposed schemes. The results show that both our multicast method and many-to-many aggregation method can efficiently reduce communication cost when delivering data to multiple mobile sinks.