Version 1
: Received: 15 March 2024 / Approved: 18 March 2024 / Online: 18 March 2024 (10:29:54 CET)
How to cite:
Hojati, M.; Roberts, S.; Robertson, C. DSTree: A Spatio-Temporal Indexing Data Structure for Distributed Networks. Preprints2024, 2024031007. https://doi.org/10.20944/preprints202403.1007.v1
Hojati, M.; Roberts, S.; Robertson, C. DSTree: A Spatio-Temporal Indexing Data Structure for Distributed Networks. Preprints 2024, 2024031007. https://doi.org/10.20944/preprints202403.1007.v1
Hojati, M.; Roberts, S.; Robertson, C. DSTree: A Spatio-Temporal Indexing Data Structure for Distributed Networks. Preprints2024, 2024031007. https://doi.org/10.20944/preprints202403.1007.v1
APA Style
Hojati, M., Roberts, S., & Robertson, C. (2024). DSTree: A Spatio-Temporal Indexing Data Structure for Distributed Networks. Preprints. https://doi.org/10.20944/preprints202403.1007.v1
Chicago/Turabian Style
Hojati, M., Steven Roberts and Colin Robertson. 2024 "DSTree: A Spatio-Temporal Indexing Data Structure for Distributed Networks" Preprints. https://doi.org/10.20944/preprints202403.1007.v1
Abstract
The widespread availability of tools to collect and share spatial data enables us to produce a large amount of geographic information on a daily basis. This enormous production of spatial data requires scalable data management systems. Geospatial architectures have changed from clusters to cloud architectures and more parallel and distributed processing platforms to be able to tackle these challenges. Peer-to-peer (P2P) systems as a backbone of distributed systems have been established in several application areas such as web3, blockchains, and crypto-currencies. Unlike centralized systems, data storage in P2P networks is distributed across network nodes, providing scalability and no single point of failure. However, managing and processing queries on these networks has always been challenging. In this work, we propose a spatio-temporal indexing data structure, DSTree. DSTree does not require additional Distributed Hash Trees (DHT) to perform multi-dimensional range queries. Inserting a piece of new geographic information updates only a portion of the tree structure and does not impact the entire graph of the data. For example, for time-series data, such as storing sensor data, the DSTree performs better. Despite the advantages of our proposed framework, challenges remain. We conclude that more significant research effort from GIScience and related fields in developing decentralized applications is needed. The need for the standardization of different geographic information when sharing data on the IPFS network is one of the requirements.
Computer Science and Mathematics, Geometry and Topology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
