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Matching game theoretical model for stable relay selection in a UAV-assisted internet of vehicles

机译:匹配游戏理论模型在无人驾驶互联网上稳定继电器选择中的理论模型

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This paper tackles the problem of selecting stable relays for Optimized Link State Routing protocol (OLSR) in urban Internet of Vehicles (IoV) in the presence of Unmanned Aerial Vehicles (UAVs). With the evolution of Internet of Things (IoT), IoV emerged from the conventional vehicular ad-hoc network to enable Vehicle to Everything (V2X) communication through different routing protocols. In OLSR protocol, Multi-Point Relays (MPRs) are selected based on their reachability and uniqueness to route information. However, urban environments are characterized by the rapid changes in topology due to the presence of intersections and traffic lights. Although clusters were proposed as a solution, selecting stable heads and MPRs are of significance, considering environment metrics to provide higher connectivity. As a solution to improve routing in IoV, a distributed Gale-Shapley matching game is proposed for stable clustering and MPR selection, utilizing nodes' quality of service (QoS). Nodes' QoS is calculated using Bayesian Belief function of stable connections utilizing environment metrics. For further enhancement in the network performance, UAVs are integrated in the network of vehicles. Conducted simulations show high percentage of stable heads and MPRs for the proposed model compared to benchmark protocols. In addition, the proposed model shows high performance in terms of packet delivery ratio, throughput and End-to-End delay, which are further improved by the presence of UAVs. (C) 2020 Elsevier Inc. All rights reserved.
机译:本文解决了无人驾驶车辆(无人机)在城市车辆(IOV)中选择优化链路状态路由协议(OLSR)的稳定继电器的问题。随着物联网(物联网)的演变,IOV从传统的车辆ad-hoc网络中出现,使车辆通过不同的路由协议来实现所有(V2X)通信。在OLSR协议中,基于其可达性和唯一性来选择多点继电器(MPRS)以路由信息。然而,城市环境的特点是由于存在交叉口和交通灯而导致的拓扑的快速变化。尽管提出了群集作为解决方案,但选择稳定的头部和MPRS具有重要意义,考虑到环境指标提供更高的连接。作为改进IOV路由路由的解决方案,提出了一个分布式的大血管匹配游戏,用于稳定聚类和MPR选择,利用节点的服务质量(QoS)。使用环境指标的稳定连接的贝叶斯信仰功能计算节点QoS。为了进一步增强网络性能,无人机集成在车辆网络中。与基准协议相比,所进行的模拟显示所提出的模型的高比例的稳定头和MPRS。此外,所提出的模型在分组传递比率,吞吐量和端到端延迟方面表现出高性能,通过无人机的存在进一步提高。 (c)2020 Elsevier Inc.保留所有权利。

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