计算机科学
计算机网络
无线自组网
优化链路状态路由协议
路由协议
网络数据包
无线路由协议
移动自组网
目的地顺序距离矢量路由
自适应服务质量多跳路由
adhoc无线分发服务
机动性模型
能源消耗
布线(电子设计自动化)
链路状态路由协议
分布式计算
无线
电信
生物
生态学
作者
Jianmin Liu,Qi Wang,ChenTao He,Katia Jaffrès‐Runser,Yuqiang Xu,Zhenyu Li,Yongjun Xu
标识
DOI:10.1016/j.comcom.2019.11.011
摘要
A network with reliable and rapid communication is critical for Unmanned Aerial Vehicles (UAVs). Flying Ad Hoc Networks (FANETs) consisting of UAVs is a new paradigm of wireless communication. However, the highly dynamic topology of FANETs and limited energy of UAVs have brought great challenges to the routing design of FANETs. It is difficult for existing routing protocols for Mobile Ad Hoc Networks (MANETs) and Vehicular Ad Hoc Networks (VANETs) to adapt the high dynamics of FANETs. Moreover, few of existing routing protocols simultaneously meet the requirement of low delay and low energy consumption of FANETs. This paper proposes a novel Q-learning based Multi-objective optimization Routing protocol for FANETs to provide low-delay and low-energy service guarantees. Most of existing Q-learning based protocols use a fixed value for the Q-learning parameters. In contrast, Q-learning parameters can be adaptively adjusted in the proposed protocol to adapt to the high dynamics of FANETs. In addition, a new exploration and exploitation mechanism is also proposed to explore some undiscovered potential optimal routing path while exploiting the acquired knowledge. Instead of using past neighbor relationships, the proposed method re-estimates neighbor relationships in the routing decision process to select the more reliable next hop. Simulation results show that the proposed method can provide higher packet arrival ratio, lower delay and energy consumption than existing good performing Q-learning based routing method.
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