Towards Exploration of Social in Social Internet of Vehicles Using an Agent-Based Simulation
Authored by Kashif Zia, Arshad Muhammad, Abbas Khalid, Ahmad Din, Alois Ferscha
Date Published: 2019
DOI: 10.1155/2019/8201396
Sponsors:
No sponsors listed
Platforms:
NetLogo
Model Documentation:
Other Narrative
Flow charts
Pseudocode
Model Code URLs:
Model code not found
Abstract
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.
Tags