International Journal of Innovative Science Engineering and Technology (IJISET)
Target tracking is one of the most important applications of wireless sensor networks that involve long-term and low-cost monitoring and actuating. In these applications, sensor nodes use batteries as the sole energy source. Therefore, energy efficiency becomes critical. When nodes operate in a duty cycling mode, tracking performance can be improved if the target motion can be predicted and nodes along the trajectory can be proactively awakened. However, this will negatively influence the energy efficiency and constrain the benefits of duty cycling. In this dissertation, probability-based prediction and sleep scheduling protocol to improve energy efficiency of proactive wake up is used.