Integration of wireless communication technologies in internet of vehicles for handover decision and network selection

Shaik Mazhar Hussain, Kamaludin Mohamad Yusof, Shaik Ashfaq Hussain

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract

Appropriate selection of networks plays a significant role in successful handovers in heterogeneous Internet of vehicles (IoV) environments. The research community is currently facing challenges about insufficient information at the mobile terminals for the efficient selection of suitable networks. Recently, some of the wireless technologies that have gained attention are DSRC, 4G LTE, and 5G. Each technology has its limitations. DSRC offers low latency but lacks spectrum availability. 4G LTE offers high bandwidth but suffers from high transmission time intervals (HTTI). 5G offers ultralow latency, ultrahigh bandwidth, and high data rates but suffers from shorter range and line-of-sight issues. Therefore, single technology cannot accommodate the requirements of vehicular communications, especially for delay-sensitive applications. Hence, there is a need to integrate multiple radio access technologies (MRATs) for efficient information exchange between vehicles to satisfy the needs of delay-sensitive and high bandwidth applications. In our work, we have proposed AI algorithms for appropriate network selection for handover and routing methods. In this chapter, we have tested our algorithms by developing three terminals onboard unit (OBU) equipped with three technologies. The proposed approach is evaluated using the OMNET ++Simulation tool. In our simulation model, we consider a heterogeneous IoV environment comprising DSRC, 4G LTE, and 5G technologies. Results obtained show that our approach has outperformed the existing approach.
Original languageEnglish
Title of host publicationIn Emerging Methodologies and Applications in Modelling, System Assurances, Academic Press
Chapter30
Pages547
Number of pages561
ISBN (Electronic)9780323902403
DOIs
Publication statusPublished - Mar 18 2022

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