An energy efficient sleep scheduling scheme using patterns based on finite field theory for wireless sensor network

The key challenge in designing wireless sensor network protocols is to provide energy efficient communication. This thesis presents an innovative code based sleep and wakeup scheduling scheme to minimize the energy consumption caused by idle listening. The proposed algorithm, SWAP, derives a set of binary patterns with a wide range of duty cycles using the mathematical properties of finite fields. Each sensor node in a network is assigned a fixed schedule generated by the SWAP, and uses it for sleep and wakeup scheduling. The scheduling pattern designed for low duty cycle sensor networks reduces the channel contention in a network by distributing the wakeup schedule of a node over the entire frame. The generated pattern also has an important characteristic that ensures a common communication slot between any two patterns in a set. To reduce the packet latency due to scheduled communication, SWAP uses a packet prioritization scheme for delay sensitive packets.;To evaluate the energy efficiency and performance of the proposed mechanism,we have implemented SWAP in TOSSIM, and compared it with a widely used channel access protocol, BMAC with LPL, in terms of packet delivery ratio, power consumption and delay. The results of our study show that SWAP performs better in terms of energy consumption while maintaining comparable packet delivery ratio and latency.