Energy-Efficient Scheduling Optimization in Wireless Sensor Networks with Delay Constraints

Energy-efficiency in wireless sensor networks is a very critical design issue, because they usually operate with tiny batteries and take a long time for replacement. In this context, we analyze the optimized scheduling strategy to minimize the energy consumed by data fusion in wireless sensor network. For implementation purpose, a low-complexity fractional-inverse- log scheduling (FILS) algorithm is presented to reduce extra significant amount of energy consumption compared to previously designed protocols. Next, in order to eliminate the communication overhead in centralized scheduling protocols, the simplified distributed fractional-inverse-log scheduling is also provided, which is shown to be very efficient in energy saving especially for a large-scale wireless sensor network. With consideration of the peak power constraint in real circuit design, we update FILS to further constrict the transmission time. Simulation results show that with peak transmission power limitation, energy consumption is still substantially reduced by FILS, and it yields more energy saving for the system with high peak-to-average power ratio (PAPR).