QMR:Q-learning based Multi-objective optimization Routing protocol for Flying Ad Hoc Networks

doi:10.1016/j.comcom.2019.11.011

	QMR:Q-learning based Multi-objective optimization Routing protocol for Flying Ad Hoc Networks
	Liu, Jianmin 1,2; Wang, Qi 1; He, ChenTao 1,2; Jaffres-Runser, Katia 3; Xu, Yida 1,2; Li, Zhenyu 1; Xu, YongJun 1
	2020-01-15
发表期刊	COMPUTER COMMUNICATIONS
ISSN	0140-3664
卷号	150 页码:304-316
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.
关键词	Multi-objective routing FANETs Q-learning Adaptive parameters
DOI	10.1016/j.comcom.2019.11.011
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China (NSFC)[61602447]
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000514749000029
出版者	ELSEVIER
引用统计	被引频次：93[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/14438
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Wang, Qi
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China 3.Univ Toulouse, IRIT ENSEEIHT, F-31061 Toulouse, France
推荐引用方式 GB/T 7714	Liu, Jianmin,Wang, Qi,He, ChenTao,et al. QMR:Q-learning based Multi-objective optimization Routing protocol for Flying Ad Hoc Networks[J]. COMPUTER COMMUNICATIONS,2020,150:304-316.
APA	Liu, Jianmin.,Wang, Qi.,He, ChenTao.,Jaffres-Runser, Katia.,Xu, Yida.,...&Xu, YongJun.(2020).QMR:Q-learning based Multi-objective optimization Routing protocol for Flying Ad Hoc Networks.COMPUTER COMMUNICATIONS,150,304-316.
MLA	Liu, Jianmin,et al."QMR:Q-learning based Multi-objective optimization Routing protocol for Flying Ad Hoc Networks".COMPUTER COMMUNICATIONS 150(2020):304-316.