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An efficient algorithm for partially matched services in internet of services

Ahmed, Mariwan; Liu, Lu; Hardy, James; Yuan, Bo; Antonopoulos, Nick

Authors

Mariwan Ahmed

Lu Liu

James Hardy

Bo Yuan

Profile image of Nick Antonopoulos

Prof Nick Antonopoulos N.Antonopoulos@napier.ac.uk
Deputy Vice Chancellor and Vice Principal of Research & Innovation



Abstract

Internet of Things (IoT) connects billions of devices in an Internet-like structure. Each device encapsulated as a real-world service which provides functionality and exchanges information with other devices. This large-scale information exchange results in new interactions between things and people. Unlike traditional web services, internet of services is highly dynamic and continuously changing due to constant degrade, vanish and possibly reappear of the devices, this opens a new challenge in the process of resource discovery and selection. In response to increasing numbers of services in the discovery and selection process, there is a corresponding increase in number of service consumers and consequent diversity of quality of service (QoS) available. Increase in both sides’ leads to the diversity in the demand and supply of services, which would result in the partial match of the requirements and offers. This paper proposed an IoT service ranking and selection algorithm by considering multiple QoS requirements and allowing partially matched services to be counted as a candidate for the selection process. One of the applications of IoT sensory data that attracts many researchers is transportation especially emergency and accident services which is used as a case study in this paper. Experimental results from real-world services showed that the proposed method achieved significant improvement in the accuracy and performance in the selection process.

Citation

Ahmed, M., Liu, L., Hardy, J., Yuan, B., & Antonopoulos, N. (2016). An efficient algorithm for partially matched services in internet of services. Personal and Ubiquitous Computing, 20(3), 283-293. https://doi.org/10.1007/s00779-016-0917-9

Journal Article Type Article
Acceptance Date Mar 30, 2016
Online Publication Date May 11, 2016
Publication Date 2016-06
Deposit Date Feb 12, 2019
Publicly Available Date Feb 12, 2019
Journal Personal and Ubiquitous Computing
Print ISSN 1617-4909
Electronic ISSN 1617-4917
Publisher BMC
Peer Reviewed Peer Reviewed
Volume 20
Issue 3
Pages 283-293
DOI https://doi.org/10.1007/s00779-016-0917-9
Keywords Emergency service selection, Quality of Service (QoS), Internet of Things (IoS), Emergency service ranking, Partial matching ,
Public URL http://researchrepository.napier.ac.uk/Output/1557161
Contract Date Feb 12, 2019

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