Agent-Based Model of Smart Social Networking-Driven Recommendations System for Internet of Vehicles

Dinesh Kumar Saini, Kashif Zia, A. Muhammad, Alois Ferscha

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

Social aspects of connectivity and information dispersion are often ignored while weighing the potential of Internet of Things (IoT). Assuming a more commonly acceptable standardization of Big Data generated by Internet of Vehicles (IoV), the social dimensions enabling its fruitful usage; emerging as Social IoV (SIoV); remains a challenge. 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 dispersion of novel information (necessary for a recommender system) substantially. It is also observed that as the network evolves as a result of incremental interactions, recommendations guaranteeing a fair distribution of vehicles across equally good competitors is not possible.
Original languageEnglish
Title of host publicationPAAMS 2018: Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity
Editors Demazeau Y., An B., Bajo J., Fernández-Caballero A.
PublisherSpringer
Pages275-287
Number of pages13
Volume10978
DOIs
Publication statusPublished - Jun 2018

Publication series

NameLecture Notes in Computer Science (LNCS)

Fields of science

  • 102 Computer Sciences
  • 102009 Computer simulation
  • 102013 Human-computer interaction
  • 102019 Machine learning
  • 102021 Pervasive computing
  • 102022 Software development
  • 102025 Distributed systems

JKU Focus areas

  • Computation in Informatics and Mathematics
  • Engineering and Natural Sciences (in general)

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