Delay-Constrained Optimal Data Aggregation in Hierarchical Wireless Sensor Networks

Abstract

A lot of realistic applications with wireless sensor networks adopt hierarchical architecture in which sensor nodes are grouped into clusters, with each cluster relying on a gateway node for local data aggregation and long-distance radio transmission. Compared to normal sensor nodes, the gateway nodes, also called application nodes (ANs), are equipped with relatively powerful transceivers and have more energy. Nevertheless, since an AN is the main gateway for sensor nodes within its clusters, its energy may be depleted more quickly than normal sensor nodes. As such, it is important to find methods to save energy for ANs. This paper presents a Delay-Constrained Optimal Data Aggregation (DeCODA) framework that considers the unique feature of traffic patterns and information processing at ANs for energy saving. Mathematical models and analytical results are provided, and simulation studies are performed to verify the effectiveness of the DeCODA framework.