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V2V Influence on M2M and H2H Traffics During Emergency Scenarios: Adaptive eNode-B for V2V Communications

V2V Influence on M2M and H2H Traffics During Emergency Scenarios: Adaptive eNode-B for V2V Communications
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Author(s): Ahmad Hani El Fawal (ENSTA Bretagne, France), Ali Mansour (ENSTA Bretagne, France) and Mohamad Najem (Beirut International University, Lebanon)
Copyright: 2020
Pages: 42
Source title: Global Advancements in Connected and Intelligent Mobility: Emerging Research and Opportunities
Source Author(s)/Editor(s): Fatma Outay (Zayed University, UAE), Ansar-Ul-Haque Yasar (Hasselt University, Belgium) and Elhadi Shakshuki (Acadia University, Canada)
DOI: 10.4018/978-1-5225-9019-4.ch003

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Abstract

This chapter envisions the challenges that will face the mobile operators such as sending vehicle-to-vehicle (V2V) payloads in form of synchronized storms, the fast saturation of the limited bandwidth of long-term evolution for machines (LTE-M) and narrow band-internet of things (NB-IoT) with the rise number of machine-to-machine (M2M) devices and V2V devices, V2V congestion overload problem in IoT environments specifically during disaster events. It extends a new solution proposed by the authors named Adaptive eNodeB (A-eNB) for both LTE-M and NB-IoT networks to deal with V2V excessive traffic. The A-eNB can solve gradually V2V overload problem, while keeping the human-to-human (H2H) traffic quality of service (QoS) not to be affected badly. It corroborates a new framework model proposed by the authors called coexistence analyzer and network architecture for long-term evolution (CANAL) to study the impact on V2V, M2M, and H2H and mutual influences, based on continuous-time Markov chain (CTMC) to simulate, analyze, and measure radio access strategies.

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