文章基本信息

标题：Prediction of Traffic on the Network at Client End Using Signal Processing
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作者：V.Vijayadeepa ; K.Baby
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2015
卷号：4
期号：8
页码：6871
DOI：10.15680/IJIRSET.2015.0408175
出版社：S&S Publications
摘要：The online shortest path problem aims at computing the shortest path based on live trafficcircumstances. 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 serversides for online shortest path computation. Unfortunately, the conventional client-server architecture scales poorly withthe number of clients. A promising approach is to let the server collect live traffic information and then broadcastthem over radio or wireless network. This approach has excellent scalability with the number of clients. Thus, wedevelop a new framework called live traffic index (LTI) which enables drivers to quickly and effectively collect thelive traffic information on the broadcasting channel. An impressive result is that the driver can compute/update theirshortest path result by receiving only a small fraction of the index. Our experimental study shows that LTI is robust tovarious 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.
关键词：LTI;Shortest path; air index; broadcasting