Opportunistic protocol based on social probability and resources efficiency for the intelligent and connected transportation system

Wang, Tong, Tang, MengBo, Song, Houbing, Cao, Yue and Khan, Zaheer (2019) Opportunistic protocol based on social probability and resources efficiency for the intelligent and connected transportation system. Computer Networks, 149. pp. 173-186. ISSN 1389-1286

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Official URL: https://doi.org/10.1016/j.comnet.2018.11.034


In recent years, Intelligent and Connected Transportation Systems (ICTS) have become a practical and valuable alternative for wide variety of novel applications in road traffic safety. It can be utilized to guarantee road safety and create new forms of inter-vehicle communications. However, due to the high speed of vehicles, the topology of the network is highly dynamic and the network may be disconnected frequently, which will lead to a decline in communication performance. Delay Tolerant Networks (DTNs) follow the approach to store and forward the message. DTNs can adapt to the highly dynamic scenario, envisioned for communication in ICTS suffering from intermittent connection. In this paper, we propose the Social Probability And Resource Effective (SPARE) protocol to improve delivery ratio and minimize the consumption of network resources. In SPARE, we focus on considering four factors that include the nodal resources effective consumption, encounter probability, nodal historical encounter information and the number of messages carried by nodes. We use the nodes’ resources efficiency and encounter probability similarity to improve the delivery ratio of SPARE algorithm. In addition, SPARE applies the mechanism of dynamically managing messages to reduce network overhead. Finally, the simulation results show that SPARE achieves a higher delivery ratio and lower overhead ratio, compared to other protocols within resource constrained network situations.

Item Type: Article
Uncontrolled Keywords: Intelligent and connected transportation systems, Delay tolerant networks, Resources efficiency, Encounter probability, Social similarity
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Elena Carlaw
Date Deposited: 18 Feb 2019 11:55
Last Modified: 31 Jul 2021 20:30
URI: http://nrl.northumbria.ac.uk/id/eprint/38060

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