Distributed spatio-temporal similarity search

In this paper we introduce the distributed spatio-temporal similarity search problem: given a query trajectory Q, we want to find the trajectories that follow a motion similar to Q, when each of the target trajectories is segmented across a number of distributed nodes. We propose two novel algorithms, UB-K and UBLB-K, which combine local computations of lower and upper bounds on the matching between the distributed subsequences and Q. Such an operation generates the desired result without pulling together all the distributed subsequences over the fundamentally expensive communication medium. Our solutions find applications in a wide array of domains, such as cellular networks, wildlife monitoring and video surveillance. Our experimental evaluation using realistic data demonstrates that our framework is both efficient and robust to a variety of conditions. Categories and Subject Descriptors H.3 [Information Storage and Retrieval]: General Terms Algorithms, Design, Performance, Experime...

• Type: Conference
• Year: 2006
• Where: CIKM
• Authors: Demetrios Zeinalipour-Yazti, Song Lin, Dimitrios Gunopulos
• Keywords: CIKM 2006, Information Management, Keywords Spatio-temporal Similarity, Similarity Search Problem, Spatio-temporal Similarity Search