An adaptive hashing technique for indexing moving objects

Authors:
Dongseop Kwon;Sangjun Lee;Wonik Choi;Sukho Lee
Affiliations:
School of Electrical Engineering and Computer Science, Seoul National University, Seoul, Korea;School of Computing, Soongsil University, Seoul, Korea;Thinkware Systems Corporation, Songpa-Gu, Seoul, Korea;School of Electrical Engineering and Computer Science, Seoul National University, Seoul, Korea
Venue:
Data & Knowledge Engineering
Year:
2006

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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 hashing 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 experimental results which show that the proposed approach is more suitable than the basic hashing under the dynamic workload.