Performance Comparison of Proposed Lifetime Maximizing Trees for Data Aggregation in Wireless Sensor Networks

In this paper the performance of the proposed DLMT and CLMT algorithms are compared. These proposed algorithms tend to extend the node lifetime. Decentralized lifetime maximizing tree(DLMT) features in nodes with higher energy to be chosen as data aggregating parents while Centralized Lifetime Maximizing Tree(CLMT) features with the identification of the bottleneck node to collect data in a central manner among given set of nodes. Simulation results show that the functional lifetime is enhanced by 147% when data is aggregated via DLMT and by 139% when data is aggregated via CLMT. Proposed DLMT algorithm has shown 13% additional lifetime saving without increasing the delay. Packet delivery ratio show remarkable increase when the tree depth is considered in these tree structures. KeywordsWireless Sensor Networks, Data aggregation, E-Span, Network lifetime, Branch energy