In this paper, we propose an energy efficient MAC protocol for wireless sensor networks. In sensor networks, reducing energy consumption is one of the critical issues for extending network lifetime. One good solution to resolve this issue is introducing listen-sleep cycles, allowing sensor nodes to turn their transceiver off during sleep periods, which was adopted by S-MAC [1]. However, in S-MAC, due to the synchronized scheduling, transmission collisions will increase in heavy traffic situations, resulting in energy waste and low throughput. Hence, in this paper, we propose probabilistic scheduled MAC (PS-MAC), in which each node determines ‘listen’ or ‘sleep’ pseudo-randomly based on its own pre-wakeup probability and pre-wakeup probabilities of its neighbor nodes in each time slot. This allows the listen-sleep schedule of nodes in each transmitter and receiver pair to be synchronized, while maintaining those of the rest of nodes to be asynchronous. Therefore, collisions can be reduced even under heavy traffic conditions, resulting in reduced energy waste and high throughput. In addition, by dynamically adjusting the pre-wakeup probabilities of sensor nodes based on the change of the network environment, system throughput and latency can be further improved. Simulation results show that PS-MAC provides significant energy savings, low delay, and high network throughput.

In this paper, we design an adaptive mobility-supporting MAC (AM-MAC) protocol for mobile sensor networks. In our protocol, as in S-MAC [1], each virtual cluster that consists of a subset of sensor nodes has its own listen-sleep schedule. Hence, when a mobile sensor node moves into a new virtual cluster, it needs to adapt to the listen-sleep schedule of the corresponding virtual cluster in a timely and energy efficient manner. To this end, in our protocol, we utilize schedule information on border nodes between virtual clusters. This allows us to implement fast and energy efficient listen-sleep schedule adaptation for mobile nodes, which consists of two main functions: energy efficient secondary listen period and smart scheduling adaptation. Simulation results show that our protocol can provide fast schedule adaptation while achieving energy efficiency.