Towards online shortest path computation

Leong Hou U, Hong Jun Zhao, Man Lung Yiu, Yuhong Li, Zhiguo Gong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

28 Citations (Scopus)

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.
Original languageEnglish
Article number6678359
Pages (from-to)1012-1025
Number of pages14
JournalIEEE Transactions on Knowledge and Data Engineering
Volume26
Issue number4
DOIs
Publication statusPublished - 1 Jan 2014

Keywords

  • Air index
  • Broadcasting
  • Shortest path

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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