An evolutionary algorithm for data aggregation tree construction in three-dimensional wireless sensor networks

Abstract

In wireless sensor networks, sensor nodes send environmental data to the sink or base station via a single hop or multiple hops. Due to limited resources, constructing a good routing path to prolong the network lifetime is critical to its effectiveness. One approach is using data aggregation techniques, where sensors aggregate data through multiple levels before reaching the base station, to reduce energy consumption. A data aggregation tree describes the flow of data from each sensor node to the sink or base station. In this paper, we study the problem of constructing a data aggregation tree optimizing four objectives: total energy consumption, network lifetime, latency and interference. This problem was proven to be NP-hard. We propose a tree-based evolutionary approach with edge-set representation, named KGASL, to solve the problem. Experimental validation on our benchmarks have been carried out to demonstrate proposed algorithm’s performance.