The paper 'A Spatial LSM Tree for Indexing Blockchain-Based Geospatial Point Data', by graduate students Seo Min-jun (first author; supervisor: Professor Jung Sung-won) and Kwon Tae-hyun (supervisor: Professor Jung Sung-won) of the Department of Computer Science & Engineering, received the Best Paper Award in the database field at the 2021 Korea Software Congress (KSC2021), held on 20 December 2021.

▲ From left: Seo Min-jun (master's, 3rd semester), Kwon Tae-hyun (master's, 2nd semester) and Professor Jung Sung-won (supervisor)

▲ Best Paper Award at the 2021 Korean Institute of Information Scientists and Engineers conference

Blockchain technology has drawn attention for its wide applicability in fields such as IoT and healthcare, and is also used as an alternative to distributed databases. Despite blockchain's high applicability, techniques for efficiently indexing blockchain-based geospatial data have seen little research to date. This paper therefore proposes a spatial LSM tree indexing technique that reflects blockchain's write-intensive character and reduces the I/O cost of inserting geospatial data in a blockchain environment. The proposed technique linearizes geospatial data using Geohash on a blockchain subject to large volumes of real-time updates, and minimizes I/O cost on insertion by taking account of spatial proximity between data. It also proposes a spatial filter that minimizes I/O cost when processing geospatial point data search queries, reducing unnecessary traversal of the spatial LSM tree.

The 2021 Korea Software Congress (KSC 2021) is an information science and technology conference at which the latest research results across every area of information technology — artificial intelligence, computer systems, databases and more — are presented.