Enabling cognitive contributory societies using SIoT: QoS aware real-time virtual object management

Zia Ush Shamszaman, Muhammad Intizar Ali

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Internet of things (IoT) has initiated a few interesting research directions such as Social Internet of Things(SIoT), Cloud of Things(CoT), and Edge of Things(EoT) etc. Nowadays, a large number of IoT nodes are available in our surroundings and there is a need to ensure automated access and communication among these IoT nodes. An emerging area of study is to make a social platform for IoT nodes so that devices can communicate with each other and create automated and on-demand services. As these IoT nodes and services are going to co-exist with us (human), we foresee establishing of cognitive contributory skills where IoT nodes, services and even human skills can collectively form a cognitive society to share resources, information and skills. However, building such intelligent societies automatically using SIoT is a big challenge, mainly due to the complexity of the systems and availability of a large number of nodes. In such scenarios, it is not trivial to find a suitable SIoT service node correctly to avail a service in real-time. We propose a common platform to virtualize the physical objects and make them available in the cyber-world and at the same time to ensure resource sharing. In this paper, we focus on virtual object management and selection process for SIoT platform. We propose a QoS aware object selection using Integer Programming solutions to find a right service at the right time.

Original languageEnglish
Pages (from-to)61-68
Number of pages8
JournalJournal of Parallel and Distributed Computing
Volume123
DOIs
Publication statusPublished - 1 Jan 2019

Bibliographical note

Funding Information:
This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 , co-funded by the European Regional Development Fund . Zia Ush Shamszaman has received his B.Sc. degree from the Computer Science dept. National University, Bangladesh in 2005 and Master of Engineering (ME) degree from dept. of ICE, Hankuk University of Foreign Studies, South Korea in 2013. Currently he is a Ph.D. candidate in the Insight Centre for Data Analytics, College of Engineering and Informatics, NUI Galway, Ireland. His research interest includes IoT, SIoT, real-time data analysis, semantic web and query processing. He is currently working on IoT and SIoT application driven real-time stream processing middleware. His contact email is, zia.shamszaman@insightcentre.org . Dr. Muhammad Intizar Ali is an Adjunct Lecturer, Research Fellow and Research Unit Leader of Reasoning, Querying, and IoT Data Analytics Unit at Insight Centre for Data Analytics, National University of Ireland, Galway. His research interests include Semantic Web, Data Integration, Internet of Things (IoT), Linked Data, Federated Query Processing, Stream Query Processing and Optimal Query Processing over large scale distributed data sources. He is actively involved in various EU funded and industry-funded projects aimed at providing IoT enabled adaptive intelligence for smart city applications and smart enterprise communication systems. He is serving as a PC member of various journals, international conferences and workshops. Dr. Ali obtained his Ph.D. (with distinction) from Vienna University of Technology, Austria in 2011. He can be contacted at ali.intizar@insight-centre.org

Publisher Copyright:
© 2018 Elsevier Inc.

Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.

Fingerprint Dive into the research topics of 'Enabling cognitive contributory societies using SIoT: QoS aware real-time virtual object management'. Together they form a unique fingerprint.

Cite this