Please use this identifier to cite or link to this item:
Scopus Web of Science® Altmetric
Type: Journal article
Title: Facilitating efficient object tracking in large-scale traceability networks
Author: Wu, Y.
Sheng, Q.
Ranasinghe, D.
Citation: The Computer Journal, 2011; 54(12):2053-2071
Publisher: Oxford University Press (OUP)
Issue Date: 2011
ISSN: 0010-4620
Statement of
Yanbo Wu, Quan Z. Sheng and Damith C. Ranasinghe
Abstract: With recent advances in technologies such as radio-frequency identification and new standards such as the electronic product code, large-scale traceability is emerging as a key differentiator in a wide range of enterprise applications (e.g. counterfeit prevention, product recalls and pilferage reduction). Such traceability applications often need to access data collected by individual enterprises in a distributed environment. Traditional centralized approaches (e.g. data warehousing) are not feasible for these applications due to their unique characteristics such as large volume of data and sovereignty of the participants. In this paper, we describe an approach that enables applications to share traceability data across independent enterprises in a pure peer-to-peer (P2P) fashion. Data are stored in local repositories of participants and indexed in the network based on structured P2P overlays. In particular, we present a generic approach for efficiently indexing and locating individual objects in large, distributed traceable networks, most notably, in the emerging environment of the internet of things. The results from extensive experiments show that our approach scales well in both data volume and network size. A real-world returnable assets management system is also developed using the proposed techniques to demonstrate its feasibility.
Keywords: Internet of things
traceable networks
radio-frequency identification
peer-to-peer systems
Rights: © The Author 2011. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved
DOI: 10.1093/comjnl/bxr105
Grant ID:
Published version:
Appears in Collections:Aurora harvest 5
Computer Science publications

Files in This Item:
File Description SizeFormat 
  Restricted Access
Restricted Access1.8 MBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.