飞行 ad hoc 网络中的自适应多路径贪婪周边无状态路由协议

IF 5.8 2区 计算机科学 Q1 TELECOMMUNICATIONS
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引用次数: 0

摘要

近年来,由无人飞行器(UAV)组成的飞行特设网络(FANET)因其在军事和民用领域的众多应用而吸引了学术界和工业研究界的关注。FANET 具有独特的特点,包括高度移动的无人机和动态拓扑结构。因此,现有的大多数路由协议,如贪婪周边无状态路由(GPSR),都与 FANET 环境及其特殊功能不兼容。要提高 GPSR 在 FANET 中的性能,必须解决几个难题,即选择合适的时间段在网络中广播 hello 消息、选择合适的标准来选择下一跳节点,以及提高数据传输过程的可靠性。本文在 FANET 中提出了一种自适应多路径贪婪周边无状态路由(AM-GPSR)协议。它包括两种新策略,即自适应你好策略和多路径贪婪转发策略。自适应打招呼策略根据无人机的速度以及两个估计位置和实际位置之间的误差,为每个无人机定义一个特殊的打招呼广播周期。此外,贪婪转发策略对候选节点进行过滤操作,剔除边界无人机和远离目的地的无人机。然后,根据到达目的地的时间和缓冲区容量对候选无人机进行优先级排序,选择优先级较高的无人机发送数据包。最后,AM-GPSR 采用贪婪多路径转发策略,以提高数据传输过程的可靠性。最后,通过网络模拟器第二版(NS2)对 AM-GPSR 进行了仿真,以评估其性能。评估过程包括两种不同的情况,即无人机速度的变化和通信范围的变化。在此过程中,AM-GPSR 与其他三种方法进行了比较,即空中贪婪地理路由协议(AGGR)、地理定位辅助航空路由协议(AeroRP)和 GPSR。比较结果表明,AM-GPSR 在传送成功率、吞吐量和延迟方面表现出色。虽然所提方法的控制开销比 AGGR 大,但其性能却优于 AGGR。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An adaptive and multi-path greedy perimeter stateless routing protocol in flying ad hoc networks

In recent years, flying ad hoc networks (FANET), formed from unmanned aerial vehicles (UAVs), have absorbed the attention of academic and industrial research communities due to their many applications in military and civilian fields. FANETs benefit from unique features, including highly moving UAVs and dynamic topological structure. Therefore, most existing routing protocols, such as the greedy perimeter stateless routing (GPSR), are not compatible with the FANET environment and its specific features. To improve the performance of GPSR in FANET, it is important to address several challenges, namely the selection of the right period for broadcasting hello messages in the network, the selection of the right criteria for selecting the next-hop node, and the improvement of reliability in the data transfer process. In this paper, an adaptive and multi-path greedy perimeter stateless routing (AM-GPSR) protocol is suggested in FANETs. It includes two new strategies, namely adaptive hello strategy and multi-path greedy forwarding strategy. The adaptive hello strategy defines a special hello broadcast period for each UAV according to its speed and error between two estimated and actual positions. Furthermore, the greedy forwarding strategy carries out a filtering operation on candidate nodes and eliminates border UAVs and those that are far from the destination. Then, candidate UAVs are prioritized based on the time to reach the destination and buffer capacity, and UAVs with higher priorities are chosen to send data packets. Finally, AM-GPSR applies a greedy multi-path forwarding strategy to increase reliability in the data transmission process. Lastly, the simulation of AM-GPSR is done via the network simulator version 2 (NS2) to evaluate its performance. This evaluation process includes two different scenarios, i.e. change in the speed of UAVs and change in their communication range. In this process, AM-GPSR is compared with three other methods, namely the aerial greedy geographic routing (AGGR) protocol, the geolocation assisted aeronautical routing protocol (AeroRP), and GPSR. This comparison shows the successful performance of AM-GPSR in terms of delivery success rate, throughput, and delay. Although the control overhead of the proposed method is more than that of AGGR.

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来源期刊
Vehicular Communications
Vehicular Communications Engineering-Electrical and Electronic Engineering
CiteScore
12.70
自引率
10.40%
发文量
88
审稿时长
62 days
期刊介绍: Vehicular communications is a growing area of communications between vehicles and including roadside communication infrastructure. Advances in wireless communications are making possible sharing of information through real time communications between vehicles and infrastructure. This has led to applications to increase safety of vehicles and communication between passengers and the Internet. Standardization efforts on vehicular communication are also underway to make vehicular transportation safer, greener and easier. The aim of the journal is to publish high quality peer–reviewed papers in the area of vehicular communications. The scope encompasses all types of communications involving vehicles, including vehicle–to–vehicle and vehicle–to–infrastructure. The scope includes (but not limited to) the following topics related to vehicular communications: Vehicle to vehicle and vehicle to infrastructure communications Channel modelling, modulating and coding Congestion Control and scalability issues Protocol design, testing and verification Routing in vehicular networks Security issues and countermeasures Deployment and field testing Reducing energy consumption and enhancing safety of vehicles Wireless in–car networks Data collection and dissemination methods Mobility and handover issues Safety and driver assistance applications UAV Underwater communications Autonomous cooperative driving Social networks Internet of vehicles Standardization of protocols.
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