Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23878
Title: Towards online shortest path computation
Authors: U, LH
Zhao, HJ
Yiu, ML 
Li, Y
Gong, Z
Keywords: Air index
Broadcasting
Shortest path
Issue Date: 2014
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on knowledge and data engineering, 2014, v. 26, no. 4, 6678359, p. 1012-1025 How to cite?
Journal: IEEE transactions on knowledge and data engineering 
Abstract: The online shortest path problem aims at computing the shortest path based on live traffic circumstances. This is very important in modern car navigation systems as it helps drivers to make sensible decisions. To our best knowledge, there is no efficient system/solution that can offer affordable costs at both client and server sides for online shortest path computation. Unfortunately, the conventional client-server architecture scales poorly with the number of clients. A promising approach is to let the server collect live traffic information and then broadcast them over radio or wireless network. This approach has excellent scalability with the number of clients. Thus, we develop a new framework called live traffic index (LTI)which enables drivers to quickly and effectively collect the live traffic information on the broadcasting channel. An impressive result is that the driver can compute/update their shortest path result by receiving only a small fraction of the index. Our experimental study shows that LTI is robust to various parameters and it offers relatively short tune-in cost (at client side), fast query response time (at client side), small broadcast size (at server side), and light maintenance time (at server side)for online shortest path problem.
URI: http://hdl.handle.net/10397/23878
ISSN: 1041-4347
EISSN: 1558-2191
DOI: 10.1109/TKDE.2013.176
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