An adaptive hashing technique for indexing moving objects q Dongseop Kwon a, * , Sangjun Lee b , Wonik Choi c , Sukho Lee a a School of Electrical Engineering and Computer Science, Seoul National University, San 56-1, Shilim-dong, Kwanak-gu, Seoul 151-742, Korea b School of Computing, Soongsil University, Seoul 156-743, Korea c Thinkware Systems Corporation, 15FL., Hanmi Tower, 45 Bangi-Dong, Songpa-Gu, Seoul 138-724, Korea Received 12 March 2005; received in revised form 12 March 2005; accepted 14 April 2005 Available online 16 May 2005 Abstract Although hashing techniques are widely used for indexing moving objects, they cannot handle the dynamic workload, e.g. the traffic at peak hour vs. that in the night. This paper proposes an adaptive hash- ing technique to support the dynamic workload efficiently. The proposed technique maintains two levels of the hashes, one for fast moving objects and the other for quasi-static objects. A moving object changes its level adaptively according to the degree of its movement. We also present the theoretical analysis and exper- imental results which show that the proposed approach is more suitable than the basic hashing under the dynamic workload. Ó 2005 Elsevier B.V. All rights reserved. Keywords: Moving objects; Spatio-temporal databases; Index structures 0169-023X/$ - see front matter Ó 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.datak.2005.04.004 q This work was supported in part by the Brain Korea 21 Project and in part by the Ministry of Information and Communications, Korea, under the Information Technology Research Center (ITRC) Support Program in 2005. * Corresponding author. E-mail addresses: dongseop@gmail.com (D. Kwon), freude@db.snu.ac.kr (S. Lee), styxii@db.snu.ac.kr (W. Choi), shlee@snu.ac.kr (S. Lee). www.elsevier.com/locate/datak Data & Knowledge Engineering 56 (2006) 287–303