Construction of Optimal Trees for Maximizing Aggregation Information in Deadline- and Energy-Constrained Unreliable Wireless Sensor Networks

In existing studies, the problem of maximizing aggregation information based on a given particular tree in deadline- and energy-constrained unreliable wireless sensor networks was addressed. However, these studies did not consider the effect of the aggregation tree structure on the maximum available aggregation information, which in this paper is proved to be important. In this paper, we focus on constructing optimal trees for maximizing aggregation information in unreliable sensor networks under a deadline constraint imposed on the sink and the energy constraints of each sensor. First, we propose an adaptive scheduling algorithm that efficiently implements scheduling in a given aggregation tree to maximize aggregation information. Second, we propose a distributed efficient algorithm to construct optimal aggregation trees and describe the design of an efficient state transition method of Markov chain that is implemented in the algorithm. Finally, we verify the performance of our proposed algorithms in a set of representative simulation scenarios. The experimental results show that, as compared with the methods examined in the existing research studies, our proposed algorithms significantly improve the maximum available aggregation information.