ABSTRACT
The storage and manipulation of road network graphs are critical to navigational and location-based services. The widespread use of GPS devices combined with low-cost storage has enabled portable and embedded systems to handle several spatiotemporal operations against a natively-stored version of the road network graph. However, the increase in amount of map detail data over the years poses several challenges for such systems. In this paper, we highlight the need for adoption of road network compression techniques in embedded geographic information systems. We also provide a technical overview of proposed road network compression techniques.
- Ali Khoshgozaran, Ali Khodaei, Mehdi Sharifzadeh, and Cyrus Shahabi. A hybrid aggregation and compression technique for road network databases. Knowledge and Information Systems, 17(3):265--286, 2008. Google ScholarDigital Library
- Zongyu Zhang. Vector road network compression: a prediction approach. In Proceedings of the American Society for Photogrammetry and Remote Sensing Conference, ASPRS, Reno, Nevada, USA, May 2006.Google Scholar
- Alexander Akimov, Alexander Kolesnikov, and Pasi Franti. Reference line approach for vector data compression. In Proceeding of the IEEE International Conference on Image Processing, ICIP, pages 1891--1894, October 2004.Google ScholarCross Ref
- Shashi Shekhar, Yan Huang, Judy Djugash, and Changqing Zhou. Vector map compression: a clustering approach. In Proceedings of the ACM International Conference on Advances in Geographic Information Systems, ACM GIS, pages 74--80, VA, USA, November 2002. Google ScholarDigital Library
- Williams, H. E., Zobel, J.: Compressing integers for fast file access. The Computer Journal 42(3), 193--201 (1999).Google ScholarCross Ref
- Suh Jonghyun, Jung Sungwon, Pfeifle Martin, Vo Khoa T, Oswald Marcus, and Reinelt Gerhard. Compression of digital road networks. In Proceedings of the International Symposium on Advances in Spatial and Temporal Databases, SSTD, pages 423--440, Massachusetts, USA, July 2007. Google ScholarDigital Library
- Nabil H. Mustafa, Shankar Krishnan, Gokul Varadhan, and Suresh Venkatasubramanian. Dynamic simplification and visualization of large maps. International Journal of Geographical Information Science, 20(3):273--302, 2006.Google ScholarCross Ref
- Alan Saalfeld. Topologically Consistent Line Simplification with the Douglas-Peucker Algorithm. Cartography and Geographic Information Science, 26(1):7--18, 1999.Google ScholarCross Ref
- Shin ting Wu and Mercedes Roco Gonzales Mrquez. A Non-Self-Intersection Douglas-Peucker Algorithm. In Brazilian Symposium on Computer Graphics and Image Processing, SIBGRAPI, pages 60--66, Ouro Preto, Brazil, August 2003.Google Scholar
- David H. Douglas and Thomas K. Peuker. Algorithms for the reduction of the number of points required to represent a digitized line or its caricature. The International Journal for Geographic Information and Geovisualization, Cartographica, 10(2):112--122, 1973.Google ScholarCross Ref
- Ali Khoshgozaran, Ali Khodaei, Mehdi Sharifzadeh, and Cyrus Shahabi. A multi-resolution compression scheme for efficient window queries over road network databases. In the International Workshop on Spatial and Spatio-temporal Data Mining, pages 355--360, December 2006. Google ScholarDigital Library
- Michela Bertolotto and Max J. Egenhofer. Progressive transmission of vector map data over the world wide web. Geoinformatica 5(4):345--373, 2001. Google ScholarDigital Library
- Barbara Buttenfield. Transmitting vector geospatial data across the internet. In Proceeding of the International Conference on Geographic Information Science, GIScience, pages 51--64, 2002. Google ScholarDigital Library
- Xavier Barillot, Jean-François Hangouet, and Hakima Kadridahmani, Generalization of the Douglas and Peucker Algorithm for Cartographic Applications, in proceedings of the 20th International Cartographic Conference, ICC, Beijing, China, August 2001.Google Scholar
- D. Solomon, Data Compression: The Complete Reference, 2nd edition, Springer-Verlag, 2000. Google ScholarDigital Library
- Minjie Chen, Mantao Xu, and Pasi Frnti. Fast dynamic quantization algorithm for vector map compression. In Proceeding of the IEEE International Conference on Image Processing, ICIP, 2010.Google ScholarCross Ref
Index Terms
Road network compression techniques in spatiotemporal embedded systems: a survey
Recommendations
Road network simplification for location-based services
AbstractRoad-network data compression or simplification reduces the size of the network to occupy less storage with the aim to fit small form-factor routing devices, mobile devices, or embedded systems. Simplification (a) reduces the storage cost of ...
A Semi-Automated System for Exploring and Fixing OSM Connectivity
SIGSPATIAL '20: Proceedings of the 28th International Conference on Advances in Geographic Information SystemsAs an open license project, Open Street Map (OSM) aims to make the collectively produced geographic data freely available to be used for various purposes. Routing engines frequently take advantage of this data set. Nonetheless, providing routing ...
Compiler-Based Code Compression for Hard Real-Time Systems
SCOPES '19: Proceedings of the 22nd International Workshop on Software and Compilers for Embedded SystemsReal-Time Systems often come with additional requirements apart from being functionally correct and adhering to their timing constraints. Another common additional optimization goal is to meet code size requirements. Code compression techniques might be ...
Comments