Data aggregation techniques have emerged as promising solutions for extending Wireless Sensor Networks (WSNs) lifetime. However, this approach suffers from a design issue in delivering the strict requirements needed by some monitoring applications. Carefully balancing Energy, Delay and Accuracy is essential for achieving these requirements. In this work, we focus on distributed data aggregation, where a sensor estimates the network information by the exchange of readings with different priority levels. We then propose an optimal decision policy for scheduling the transmission of the aggregated data at the node level. To model the investigated problem, we first adopt Markov Decision Process (MDP) whereby we define the reward function. Then, we apply a Genetic Algorithm (GA) to find a set of optimal decisions that ensures the best trade-off between energy saving, delay and accuracy of the received data based on their priority level. The simulation results yield excellent performance and our optimization shows a significant enhancement up to 20% compared to the other policies.
|Title of host publication
|2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, PIMRC 2015
|Institute of Electrical and Electronics Engineers Inc.
|Number of pages
|Published - 3 Dec 2015
|26th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications - Hong Kong, China
Duration: 30 Aug 2015 → 2 Sep 2015
Conference number: 26
|26th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications
|30/08/15 → 2/09/15