Yazar "Alkhayyat, A." seçeneğine göre listele

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    Energy Efficient Improving Routing Model for UAVs Assisted Vehicular Adhoc Networks
    (Institute of Electrical and Electronics Engineers Inc., 2023) Alsalamy, A.; Abedi, F.; Abbas, F.H.; Noori, M.S.; Alkhafaji, M.A.; Alkhayyat, A.; Alani, S.
    Vehicular Adhoc Networks (VANETs) have widespread applications in intelligent transportation systems, serving diverse purposes. These networks are characterized by their dynamic nature, which unfortunately leads to communication instability, causing increased energy consumption, delays, and routing overhead. To overcome obstacles at ground level, Unmanned Aerial Vehicles (UAVs) are introduced, enabling data transmission through an aerial medium, free from ground-level obstructions. However, for effective communication in UAV-assisted VANETs, a reliable routing protocol is essential. This paper proposes an improved routing model for UAV-assisted VANETs, called IUAVA-RP, which employs parameter-based routing and optimal path selection. The optimal path selection is performed using a decision-making process, resulting in highly effective and optimal routing for efficient data transmission. The proposed IUAVA-RP protocol is simulated using NS2 and SUMO, and its performance analysis includes parameters such as: energy efficiency, packet delivery ratio, end-to-end delay, and routing overhead. Comparative analysis is conducted with two existing protocols, HGFA-RP and AOMDV-RP. The results demonstrate that the proposed IUAVA-RP protocol achieves higher energy efficiency and packet delivery ratio, as well as lower end-to-end delay and routing overhead compared to the earlier protocols. © 2023 IEEE.
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    Mobility and Resource Allocation with Intelligent Clustering in UAVs Assisted VANETs
    (Institute of Electrical and Electronics Engineers Inc., 2023) Mahmood, S.N.; Al-Dolaimy, F.; Alkhayyat, A.; Alani, S.; Alkhafaji, M.A.; Abbas, F.H.; Guneser, M.T.
    In the past decade, there has been significant development and utilization of Unmanned Aerial Vehicles (UAVs) in Vehicular Ad Hoc Networks (VANETs) across various applications. The integration of UAVs in VANETs has provided vehicles with enhanced performance by enabling communication through an aerial medium, thereby bypassing ground-level obstacles. Efficient management of mobility and network resources becomes crucial when dealing with a large number of highly dynamic vehicles. To address this, the proposed approach in this paper is Mobility and Resource Allocation with Intelligent Clustering in UAVs-assisted VANETs (MRAIC-UAVs). The key components of the proposed approach include the network model, mobility model, clustering strategy, and UAVs Cluster Head (CH) selection process. The selection of CHs is based on the evaluation of parameters such as residual energy, UAVs mobility, UAVs degree difference, distance, and UAVs stability. This approach significantly improves network energy efficiency and packet delivery ratio. The simulation is conducted using OMNET++ with the SUMO mobility generator, and a comparison is made with earlier models such as PRO-UAVs and RJEDC-UAVs. The performance analysis considers parameters such as packet delivery ratio, end-to-end delay, energy efficiency, and energy consumption. The simulation results demonstrate that the proposed MRAIC-UAVs approach achieves higher energy efficiency and packet delivery ratio while exhibiting lower end-to-end delay and energy consumption compared to earlier approaches. © 2023 IEEE.