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Title:
An efficient location reporting and indexing framework for urban road moving objects
Author: Han, Jingyu (1) ; Chen, Kejia (1) ; Ding, Zhiming (2) ; Cao, Huiping (3)
Corresponding Author: Han, J.(jyhan@njupt.edu.cn)
Keyword: Moving objects ; Group-movement patterns ; Location reporting ; Index maintenance ; Local links ; Long-distance links
Source: Distributed and Parallel Databases
Issued Date: 2014
Volume: 32, Issue:2, Pages:271-311
Indexed Type: SCI ; EI
Department: (1) College of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, China; (2) Institute of Software, Chinese Academy of Science, Beijing 100080, China; (3) Department of Computer Science, New Mexico State University, Las Cruces, United States
Abstract: The tracking of moving objects consists of two critical operations: location reporting, in which moving objects (or clients) send their locations to centralized servers, and index maintenance, through which centralized servers update the locations of moving objects. In existing location reporting techniques, each moving object reports its locations to servers by utilizing long-distance links such as 3G/4G. Corresponding to this location reporting strategy, servers need to respond to all the location updating requests from individual moving objects. Such techniques suffer from very high communication cost (due to the individual reporting using long-distance links) and high index update I/Os (due to the massive amount of location updating requests). In this paper, we present a novel Group-movement based location Reporting and Indexing (GRI) framework for location reporting (at moving object side) and index maintenance (at server side). In the GRI framework, we introduce a novel location reporting strategy which allows moving objects to report their locations to servers in a group (instead of individually) by aggregating the moving objects that share similar movement patterns through wireless local links (such as WiFi). At the server side, we present a dual-index, Hash-GTPR-tree (H-GTPR), to index objects sharing similar movement patterns. Our experimental results on synthetic and real data sets demonstrate the effectiveness and efficiency of our new GRI framework, as well as the location reporting strategy and the H-GTPR tree index technique. © 2013 Springer Science+Business Media New York.
English Abstract: The tracking of moving objects consists of two critical operations: location reporting, in which moving objects (or clients) send their locations to centralized servers, and index maintenance, through which centralized servers update the locations of moving objects. In existing location reporting techniques, each moving object reports its locations to servers by utilizing long-distance links such as 3G/4G. Corresponding to this location reporting strategy, servers need to respond to all the location updating requests from individual moving objects. Such techniques suffer from very high communication cost (due to the individual reporting using long-distance links) and high index update I/Os (due to the massive amount of location updating requests). In this paper, we present a novel Group-movement based location Reporting and Indexing (GRI) framework for location reporting (at moving object side) and index maintenance (at server side). In the GRI framework, we introduce a novel location reporting strategy which allows moving objects to report their locations to servers in a group (instead of individually) by aggregating the moving objects that share similar movement patterns through wireless local links (such as WiFi). At the server side, we present a dual-index, Hash-GTPR-tree (H-GTPR), to index objects sharing similar movement patterns. Our experimental results on synthetic and real data sets demonstrate the effectiveness and efficiency of our new GRI framework, as well as the location reporting strategy and the H-GTPR tree index technique. © 2013 Springer Science+Business Media New York.
Language: 英语
WOS ID: WOS:000335571000003
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/16862
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Han, Jingyu ,Chen, Kejia ,Ding, Zhiming ,et al. An efficient location reporting and indexing framework for urban road moving objects[J]. Distributed and Parallel Databases,2014-01-01,32(2):271-311.
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