Towards Exploration of Social in Social Internet of Vehicles Using an Agent-Based Simulation

Internet of Vehicles (IoV) is turning out to be one of the first impressive examples of Internet of Things (IoT). In IoV, the factors of connectivity and interaction/information dispersion are equally important as sensing/actuating, context-awareness, services provisioning, etc. However, most of the...

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Main Authors: Kashif Zia, Arshad Muhammad, Abbas Khalid, Ahmad Din, Alois Ferscha
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2019/8201396
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author Kashif Zia
Arshad Muhammad
Abbas Khalid
Ahmad Din
Alois Ferscha
author_facet Kashif Zia
Arshad Muhammad
Abbas Khalid
Ahmad Din
Alois Ferscha
author_sort Kashif Zia
collection DOAJ
description Internet of Vehicles (IoV) is turning out to be one of the first impressive examples of Internet of Things (IoT). In IoV, the factors of connectivity and interaction/information dispersion are equally important as sensing/actuating, context-awareness, services provisioning, etc. However, most of the researches related to connectivity and interaction are constrained to physics of signaling and data science (semantics/contents), respectively. Very rapidly, the meanings of these factors are changing due to evolution of technologies from physical to social domain. For example, Social IoV (SIoV) is a term used to represent when vehicles build and manage their own social network. Hence, in addition to physical aspects, the social aspects of connectivity and information dispersion towards these systems of future should also be researched, a domain so far ignored in this particular context. In this paper, an agent-based model of information sharing (for context-based recommendations) of a hypothetical population of smart vehicles is presented. Some important hypotheses are tested under reasonable connectivity and data constraints. The simulation results reveal that closure of social ties and its timing impacts the dispersion of novel information (necessary for a recommender system) substantially. It is also observed that as the network evolves due to incremental interactions, the recommendations guaranteeing a fair distribution of vehicles across equally good competitors is not possible.
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institution Kabale University
issn 1076-2787
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publishDate 2019-01-01
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series Complexity
spelling doaj-art-5e1582bbb26744ad945bb5328aaf56432025-02-03T01:12:51ZengWileyComplexity1076-27871099-05262019-01-01201910.1155/2019/82013968201396Towards Exploration of Social in Social Internet of Vehicles Using an Agent-Based SimulationKashif Zia0Arshad Muhammad1Abbas Khalid2Ahmad Din3Alois Ferscha4Faculty of Computing and Information Technology, Sohar University, Sohar, OmanFaculty of Computing and Information Technology, Sohar University, Sohar, OmanDepartment of Computer Science and Information Technology, The University of Lahore, PakistanDepartment of Computer Science, COMSATS University Islamabad (CUI), Abbottabad Campus, PakistanInstitute of Pervasive Computing, University of Linz, AustriaInternet of Vehicles (IoV) is turning out to be one of the first impressive examples of Internet of Things (IoT). In IoV, the factors of connectivity and interaction/information dispersion are equally important as sensing/actuating, context-awareness, services provisioning, etc. However, most of the researches related to connectivity and interaction are constrained to physics of signaling and data science (semantics/contents), respectively. Very rapidly, the meanings of these factors are changing due to evolution of technologies from physical to social domain. For example, Social IoV (SIoV) is a term used to represent when vehicles build and manage their own social network. Hence, in addition to physical aspects, the social aspects of connectivity and information dispersion towards these systems of future should also be researched, a domain so far ignored in this particular context. In this paper, an agent-based model of information sharing (for context-based recommendations) of a hypothetical population of smart vehicles is presented. Some important hypotheses are tested under reasonable connectivity and data constraints. The simulation results reveal that closure of social ties and its timing impacts the dispersion of novel information (necessary for a recommender system) substantially. It is also observed that as the network evolves due to incremental interactions, the recommendations guaranteeing a fair distribution of vehicles across equally good competitors is not possible.http://dx.doi.org/10.1155/2019/8201396
spellingShingle Kashif Zia
Arshad Muhammad
Abbas Khalid
Ahmad Din
Alois Ferscha
Towards Exploration of Social in Social Internet of Vehicles Using an Agent-Based Simulation
Complexity
title Towards Exploration of Social in Social Internet of Vehicles Using an Agent-Based Simulation
title_full Towards Exploration of Social in Social Internet of Vehicles Using an Agent-Based Simulation
title_fullStr Towards Exploration of Social in Social Internet of Vehicles Using an Agent-Based Simulation
title_full_unstemmed Towards Exploration of Social in Social Internet of Vehicles Using an Agent-Based Simulation
title_short Towards Exploration of Social in Social Internet of Vehicles Using an Agent-Based Simulation
title_sort towards exploration of social in social internet of vehicles using an agent based simulation
url http://dx.doi.org/10.1155/2019/8201396
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