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Distributed Spatial Indexing for the Internet of Things Data Management

Fathy, Y, Barnaghi, P and Tafazolli, R (2017) Distributed Spatial Indexing for the Internet of Things Data Management In: IFIP/IEEE International Symposium on Integrated Network Management, 2017-05-08 - 2017-05-12, Lisbon, Portugal.

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Abstract

The Internet of Things (IoT) has become a new enabler for collecting real-world observation and measurement data from the physical world. The IoT allows objects with sensing and network capabilities (i.e. Things and devices) to communicate with one another and with other resources (e.g. services) on the digital world. The heterogeneity, dynamicity and ad-hoc nature of underlying data, and services published by most of IoT resources make accessing and processing the data and services a challenging task. The IoT demands distributed, scalable, and efficient indexing solutions for large-scale distributed IoT networks. We describe a novel distributed indexing approach for IoT resources and their published data. The index structure is constructed by encoding the locations of IoT resources into geohashes and then building a quadtree on the minimum bounding box of the geohash representations. This allows to aggregate resources with similar geohashes and reduce the size of the index. We have evaluated our proposed solution on a large-scale dataset and our results show that the proposed approach can efficiently index and enable discovery of the IoT resources with 65% better response time than a centralised approach and with a high success rate (around 90% in the first few attempts).

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Communication Systems Research
Authors :
AuthorsEmailORCID
Fathy, YUNSPECIFIEDUNSPECIFIED
Barnaghi, PUNSPECIFIEDUNSPECIFIED
Tafazolli, RUNSPECIFIEDUNSPECIFIED
Date : May 2017
Copyright Disclaimer : © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Contributors :
ContributionNameEmailORCID
UNSPECIFIEDIEEE, UNSPECIFIEDUNSPECIFIED
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 29 Mar 2017 10:02
Last Modified : 30 Mar 2017 13:48
URI: http://epubs.surrey.ac.uk/id/eprint/813879

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