Gathering correlated data in sensor networks

In this paper, we consider energy-efficient gathering of correlated data in sensor networks. We focus on single-input coding strategies in order to aggregate correlated data. For foreign coding we propose the MEGA algorithm which yields a minimum-energy data gathering topology in O n3 time. We also consider self-coding for which the problem of finding an optimal data gathering tree was recently shown to be NP-complete; with LEGA, we present the first approximation algorithm for this problem with approximation ratio 2(1 + √ 2) and running time O(m + n log n). Categories and Subject Descriptors: F.2.2 [Analysis of Algorithms and Problem Complexity]: Nonnumerical Algorithms and Problems—computations on discrete structures; G.2.2 [Discrete Mathematics]: Graph Theory—graph algorithms; G.2.2 [Discrete Mathematics]: Graph Theory—network problems General Terms: Algorithms, Theory.

• Type: Conference
• Year: 2004
• Where: DIALM
• Authors: Pascal von Rickenbach, Roger Wattenhofer
• Keywords: Algorithms, Correlated Data, Data Gathering, DIALM 2004