A Data-Centric Self-organization Scheme for Energy-Eﬃcient Wireless Sensor Networks SungHyup Lee 1 , YoungSoo Choi 2 , HeeDong Park 3 , YoonYoung An 2 , and YouZe Cho 2,⋆ 1 Department of Information and Communications Kyungpook National University, Korea tenetshlee@ee.knu.ac.kr 2 School of Electrical Engineering and Computer Science Kyungpook National University, Korea {yschoi, yzcho}@ee.knu.ac.kr, yyahn@etri.re.kr 3 Department of Computer Engineering Pohang college, Korea hdpark@pohang.ac.kr Abstract. In this paper, we propose a new self-organization scheme, DICSION (Data-centrIC Self-organizatION), which can improve the en- ergy eﬃciency and prolong network lifetime of wireless sensor networks. Since a large number of sensor nodes are densely deployed, neighboring nodes may be very close to each other. Therefore, we assume that sen- sor nodes have a high possibility to collect the duplicate data about the same event. DICSION can considerably reduce the energy consumption because a zone head only can transmit and receive a representative data to base station or neighboring zone heads after zone formation. Our per- formance evaluation results demonstrate that DICSION outperforms to STEM. 1 Introduction It is important to prolong network lifetime and improve energy-eﬃciency in wire- less sensor networks consisting of sensor nodes with limited energy resources [1]. Hence, in starting to organize a wireless sensor network, energy eﬃciency of sensor nodes must be considered to prolong network lifetime [2], [3], [5]. Wire- less sensor network is diﬀerent from ad hoc networks in a number of ways; hence, self-organization schemes of ad hoc networks such as GAF(Geographic Adaptive Fidelity) [6] and Span [7] do not immediately apply to wireless sensor networks. Therefore, we analyze the important characteristics and performance improvement components of previous schemes and propose a new, eﬃcient and constructive self-organization scheme for wireless sensor networks. We also provide a brief overview of major existing schemes. In ASCENT (Adaptive Self-Conﬁguring sEnsor Networks Topologies) [8], the large number ⋆ Corresponding author. X. Zhou et al. (Eds.): EUC Workshops 2006, LNCS 4097, pp. 455–464, 2006. c  IFIP International Federation for Information Processing 2006