Topology knowledge range control for lifetime maximization in sensor networks with data aggregation

Abstract

Prolonging lifetime is a key challenge in wireless sensor networks comprising unattended, limited resource sensor nodes. Since sensor networks are usually large in size, simple and scalable routing schemes are essential. Geographical routing is attractive due to its simplicity and scalability. At the same time geographical routing is not efficient from the perspectives of energy consumption and energy balancing, By appropriately selecting topology knowledge range for the sensor nodes energy efficiency can be improved and energy usage of various sensor nodes can be more balanced, leading to longer network lifetime. Different from the former work on knowledge range control where the objective is to minimize the total energy consumption in the network, our work aims at lifetime maximization which needs a tradeoff between energy efficiency and balanced energy consumption. Further, we study the problem for the networks wherein data aggregation is carried out at the nodes, Data aggregation is a commonly used operation in several sensor network applications. While data aggregation reduces load in the network leading to improved lifetime, developing efficient solutions is not trivial. We develop Mixed Integer Linear Programming (MILP) formulations for the maximum lifetime knowledge range decision problem in networks with data aggregation, and then develop a scalable distributed protocol. We verify the effectiveness of this protocol through extensive simulations. We also study the impact of data aggregation on lifetime, We make several useful observations from the numerical results obtained from CPLEX and the simulation results. Copyright 2005 ACM.