SIoTPredict

a framework for predicting relationships in the Social Internet of Things

Abdulwahab Aljubairy*, Wei Emma Zhang, Quan Z. Sheng, Ahoud Alhazmi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

Abstract

The Social Internet of Things (SIoT) is a new paradigm that integrates social network concepts with the Internet of Things (IoT). It boosts the discovery, selection and composition of services and information provided by distributed objects. In SIoT, searching for services is based on the utilization of the social structure resulted from the formed relationships. However, current approaches lack modelling and effective analysis of SIoT. In this work, we address this problem and specifically focus on modelling the SIoT’s evolvement. As the growing number of IoT objects with heterogeneous attributes join the social network, there is an urgent need for identifying the mechanisms by which SIoT structures evolve. We model the SIoT over time and address the suitability of traditional analytical procedures to predict future relationships (links) in the dynamic and heterogeneous SIoT. Specifically, we propose a framework, namely SIoTPredict, which includes three stages: i) collection of raw movement data of IoT devices, ii) generating temporal sequence networks of the SIoT, and iii) predicting relationships among IoT devices which are likely to occur. We have conducted extensive experimental studies to evaluate the proposed framework using real SIoT datasets and the results show the better performance of our framework.

Original languageEnglish
Title of host publicationAdvanced Information Systems Engineering
Subtitle of host publication32nd International Conference, CAiSE 2020 Grenoble, France, June 8–12, 2020 Proceedings
EditorsSchahram Dustdar, Eric Yu, Camille Salinesi, Dominique Rieu, Vik Pant
Place of PublicationCham, Switzerland
PublisherSpringer, Springer Nature
Pages101-116
Number of pages16
ISBN (Electronic)9783030494353
ISBN (Print)9783030494346
DOIs
Publication statusPublished - 2020
Event32nd International Conference on Advanced Information Systems Engineering, CAiSE 2020 - Grenoble, France
Duration: 8 Jun 202012 Jun 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12127 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference32nd International Conference on Advanced Information Systems Engineering, CAiSE 2020
CountryFrance
CityGrenoble
Period8/06/2012/06/20

Keywords

  • Dynamic networks
  • Edge exchangeability
  • Link prediction
  • Social Internet of Things (SIoT)

Fingerprint Dive into the research topics of 'SIoTPredict: a framework for predicting relationships in the Social Internet of Things'. Together they form a unique fingerprint.

  • Cite this

    Aljubairy, A., Zhang, W. E., Sheng, Q. Z., & Alhazmi, A. (2020). SIoTPredict: a framework for predicting relationships in the Social Internet of Things. In S. Dustdar, E. Yu, C. Salinesi, D. Rieu, & V. Pant (Eds.), Advanced Information Systems Engineering: 32nd International Conference, CAiSE 2020 Grenoble, France, June 8–12, 2020 Proceedings (pp. 101-116). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12127 LNCS). Cham, Switzerland: Springer, Springer Nature. https://doi.org/10.1007/978-3-030-49435-3_7