Vehicular Network Dynamic Grouping Scheme

Al-Hamid, Duaa Zuhair; Al-Anbuky, Adnan

doi:10.1109/acsos-c52956.2021.00080

Cited by 5 publications

(1 citation statement)

References 5 publications

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“…In scenario-III, a different variant of the routing protocol will be triggered when the entire nodes in the network are completely dynamic. Hence, in this paper, a hybrid routing protocol is being proposed to enhance the performance of the vehicular network by considering three different scenarios based on the statistical information from the AI algorithm [23]. Moreover, in the existing approaches, there is no single routing protocol that is being proposed to enhance the performance of the vehicular IoT network in terms of node mobility, channel/spectrum mobility and the channel-route maintenance [24].…”

Section: Related Workmentioning

confidence: 99%

An AI fuzzy clustering-based routing protocol for vehicular image recognition in vehicular ad hoc IoT networks

et al. 2023

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A vehicular ad-hoc IoT network (VA-IoT) plays a key role in exchanging the constrained networked vehicle information through IPv6 enabled sensor nodes. It is noteworthy to understand that vehicular IoT is interconnection of vehicular ad-hoc networks with the support of constrained IoT devices. Routing protocols in VAN-IoT is designed to route the vehicular tra c in the distributed environments. In addition, VAN-IoT is designed to enhance the road safety by reducing the number of road accidents through reliable data transmission. Routing in VAN-IoT has a unique dynamic topology, frequent spectrum, and node handover with restricted versatility. Hence, it is very crucial to design the hybrid reactive routing protocols to ensure the network throughput and data reliability of the VAN-IoT networks. This paper aims to propose an AI based Reactive Routing protocol to enhance the performance of the network throughput, minimize the end-to-end delay with respect to node mobility, spectrum mobility, link tra c load and endto-end network tra c load while transmitting the vehicular images. In addition, the performance of the proposed routing protocol in terms of image transmission time is being compared with the existing initiative-taking and reactive based routing protocols in Vehicular Adhoc IoT (VA-IoT) Networks.communicate with other neighbors that are within the range of node signal transmissions. In other words, a multi-hop communication is needed when the source and destination is being connected to different networks. Due to this, the vehicular nodes(routers) within the VA-IoT network must cooperate with each other to forward the application data from the source to the destination [7]. To transmit the information from the source to the destination, the network must be connected. In other words, nodes within the network must be capable of nding other nodes within the communication range to forward the application data from source to destination that in different geographical locations. The physical communication through radio signals is transmitted through Dedicated Short-Range Communication (DSRC) operating at 5.9GHz through IEEE 802.15.4 standard. The Wireless Access in Vehicular Environments (WAVE) is built with the speci cations based on American DSRC that divides the spectrum into seven 10 MHz channels. Since the pattern is being proposed for vehicular adhoc communication, the node velocity, signal transmission radius and data transmission rate is being predetermined within the communication medium for application data transmission [8][9][10][11].Based on the WAVE characteristics, the maximum node velocity will be up to 190 Km/hr., transmission radius is up to 1 km in noise free environment and transmission speed could be up to 27 Mbps in VANETs. The network layer in the TCP/IP protocol stack is responsible for de ning the rules of packet routing in the public switched networks. The packet routing process is de ned as the service responsible

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Section: Related Workmentioning

confidence: 99%

An AI fuzzy clustering-based routing protocol for vehicular image recognition in vehicular ad hoc IoT networks

et al. 2023

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UAV-enabled software defined data collection from an adaptive WSN

Karegar,

Al-Hamid,

Chong

2024

Wireless Netw

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Unmanned aerial vehicle (UAV)-based data gathering from wireless sensor networks is one of the recent research topics that has currently attracted research interest. One of the challenges for the UAV-aided WSN data collection efforts is to design an energy-efficient UAV/drone communication with arbitrarily dispersed ground sensors by improving the ground network structure. This paper aims to develop a technique titled UAV Fuzzy Travel Path' that supports UAV smooth path design and enables ground network topology shifting. A comprehensive UAV-based data collection model is proposed to enable dynamic orchestration/re-orchestration of wireless ground sensors to jointly improve network performance and UAV path fluidity. This provides a more flexible ground network framework that can be restructured based on network demands and UAV optimal paths, effectively allowing for a software-defined network concept. The main contribution of this work is the implementation of the software-defined wireless sensor network on the ground network that adaptably supports the movement of the UAV and enhances the communication network’s energy efficiency with a proposed latency analytical analysis via network orchestration/re-orchestration phases. The main significance of this research is in offering a flexible span for UAV path design than being fixed in one strict route for data gathering purposes. Four various simulation tools are employed for modelling and performance evaluation, namely MATLAB, CupCarbon, Contiki-Cooja and Mission Planner. The proposed software-defined ground network system demonstrates encouraging results in terms of network performance metrics including energy consumption of UAV versus ground sensor nodes energy usage, packet delivery rate, and the communication time of the ground orchestrated or/and re-orchestrated network.

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Vehicular Intelligence: Towards Vehicular Network Digital-Twin

Al-Hamid

Al-Anbuky

2022

2022 27th Asia Pacific Conference on Communications (APCC)

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Vehicular Network Dynamic Grouping Scheme

Cited by 5 publications

References 5 publications

An AI fuzzy clustering-based routing protocol for vehicular image recognition in vehicular ad hoc IoT networks

An AI fuzzy clustering-based routing protocol for vehicular image recognition in vehicular ad hoc IoT networks

UAV-enabled software defined data collection from an adaptive WSN

Vehicular Intelligence: Towards Vehicular Network Digital-Twin

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