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Vehicular Grouping and Network Formation: Virtualization of Network Self-healing

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11253))

Abstract

The enhancement of vehicular network management and connectivity can significantly improve road safety and pave the way towards unmanned vehicular operation. Variable speeds and densities associated with constant movement of vehicles, changeable routes adopted by vehicles under diverse traffic conditions, would inevitably result in different dynamic vehicular network cluster formation/re-organization possibilities. Such dynamic re-organization for vehicular networks necessitates aspects of self-formation, self-joining and self-healing. Member nodes located in close vicinity to each other may formulate a group within the network. New members may join a group in case they arrive within close proximity of the group while existing members may depart in the event of change of route or if the group become distance away. The departure of a vehicle (an active network node) may create rupture in the data communication network operation. The paper presents the organization of vehicular network considering the dynamic self-healing in the event of departure of a key network-connectivity component. The Contiki-Cooja simulation tool is used for implementation wherein various network scenarios are created to test and analyze the process. The results indicate the efficiency of election process at minimal network downtime. It also reflects how the network down time can be minimized or even totally removed using appropriate vehicular sensed parameters. The study also offers preliminary analysis to the impact of connectivity dynamics on the network re-organization process.

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Correspondence to Duaa Zuhair Al-Hamid .

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Al-Hamid, D.Z., Al-Anbuky, A. (2018). Vehicular Grouping and Network Formation: Virtualization of Network Self-healing. In: Skulimowski, A., Sheng, Z., Khemiri-Kallel, S., Cérin, C., Hsu, CH. (eds) Internet of Vehicles. Technologies and Services Towards Smart City. IOV 2018. Lecture Notes in Computer Science(), vol 11253. Springer, Cham. https://doi.org/10.1007/978-3-030-05081-8_8

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  • DOI: https://doi.org/10.1007/978-3-030-05081-8_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05080-1

  • Online ISBN: 978-3-030-05081-8

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