Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/108609
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Type: Conference paper
Title: Indexing linked data in a wireless broadcast system with 3D Hilbert space-filling curves
Author: Qin, Y.
Sheng, Q.
Falkner, N.
Zhang, W.
Wang, H.
Citation: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014 / Wang, X. (ed./s), pp.1775-1778
Publisher: ACM
Issue Date: 2014
ISBN: 978-1-4503-2598-1
Conference Name: 23rd ACM International Conference on Conference on Information and Knowledge Management (CIKM) (03 Nov 2014 - 07 Nov 2014 : Shanghai, China)
Statement of
Responsibility: 
Yongrui Qin, Quan Z. Sheng, Nickolas J.G. Falkner, Wei Emma Zhang, Hua Wang
Abstract: Semantic technologies aim to facilitate machine-to-machine communication and are attracting more and more interest from both academia and industry, especially in the emerging Internet of Things (IoT). In this paper, we consider large-scale information sharing scenarios among mobile objects in IoT by leveraging semantic techniques. We propose to broadcast Linked Data on-air using RDF format to allow simultaneous access to the information and to achieve better scalability. We introduce a novel air indexing method to reduce the information access latency and energy consumption. To build air indexes, we firstly map RDF triples in the Linked Data into points in a 3D space and build B+-trees based on 3D Hilbert curve mappings for all of the 3D points. We then convert these trees into linear sequences so that they can be broadcast over a wireless channel. A novel search algorithm is also designed to efficiently evaluate queries against the air indexes. Experiments show that our indexing method outperforms the air indexing method based on traditional 3D R-trees.
Keywords: Linked Data; wireless broadcast; air indexing
Rights: Copyright 2014 ACM
RMID: 0030028142
DOI: 10.1145/2661829.2661890
Appears in Collections:Computer Science publications

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