Latest revision as of 19:46, 1 February 2021

Abstract

To address increasing traffic congestion and its associated consequences, traffic managers are turning to intelligent transportation management. The latte project is extending data stream technology to handle queries that combine live streams with large data archives, motivated by needs in the Intelligent Transportation Systems (ITS) domain. In particular, we focus on queries that combine live data streams with large data archives. We demonstrate such stream-archive queries via the travel-time estimation problem. The demonstration uses the new latte system which has been developed using the NiagaraST stream processing system and the PORTAL transportation data archive.

Original document

The different versions of the original document can be found in:

• http://datalab.cs.pdx.edu/latte/sigmod060d-tufte.pdf

• https://dblp.uni-trier.de/db/conf/sigmod/sigmod2007.html#TufteLMPBR07,

http://datalab.cs.pdx.edu/latte/sigmod060d-tufte.pdf,

http://www.cs.pdx.edu/~tufte/papers/lattedemo.pdf,

https://dl.acm.org/citation.cfm?id=1247480.1247617,

http://portal.acm.org/citation.cfm?doid=1247480.1247617,

https://doi.org/10.1145/1247480.1247617,

https://doi.acm.org/10.1145/1247480.1247617,

https://academic.microsoft.com/#/detail/2052693416

• http://dl.acm.org/ft_gateway.cfm?id=1247617&ftid=430403&dwn=1,

http://dx.doi.org/10.1145/1247480.1247617