A New Deep Q-Network Design for QoS Multicast Routing in Cognitive Radio MANETs

In this paper, we propose a new deep Q-network (DQN) design for quality-of-service (QoS) multicast routing (DQMR) protocol to establish efficient QoS multicast (EQM) trees in cognitive radio mobile ad hoc networks (CR-MANETs). An EQM tree is a shortest-path multicast tree with minimum end-to-end (E2...

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Autores principales:	Thong-Nhat Tran, Toan-Van Nguyen, Kyusung Shim, Daniel Benevides Da Costa, Beongku An
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Cognitive mobile ad hoc networks cross-layer deep Q-network game theory QoS multicast routing Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/f3477469621944988154e01a655445c7
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id	oai:doaj.org-article:f3477469621944988154e01a655445c7
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spelling	oai:doaj.org-article:f3477469621944988154e01a655445c72021-11-20T00:02:58ZA New Deep Q-Network Design for QoS Multicast Routing in Cognitive Radio MANETs2169-353610.1109/ACCESS.2021.3126844https://doaj.org/article/f3477469621944988154e01a655445c72021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9610033/https://doaj.org/toc/2169-3536In this paper, we propose a new deep Q-network (DQN) design for quality-of-service (QoS) multicast routing (DQMR) protocol to establish efficient QoS multicast (EQM) trees in cognitive radio mobile ad hoc networks (CR-MANETs). An EQM tree is a shortest-path multicast tree with minimum end-to-end (E2E) cost (a combination of queuing size ratio and link stability) subject to QoS constraints such as queuing size ratio, link stability, number of hops, number of time slots and avoiding the licensed channel of primary users. Particularly, we propose an NP-complete optimization problem such that its feasible solution is an EQM tree. To address this problem, we design a new DQN model and a new game-based model to form EQM trees in real-time by offline training instead of online training as done in previous papers. Moreover, the DQMR protocol is also guaranteed to have high stability, low routing delay, low control overhead, and high packet delivery ratio (PDR). Furthermore, one more new contribution of the paper is that exact closed-form expressions for the E2E queuing delay of a multicast routing tree are also derived assuming random waypoint mobility and the reference point group mobility models to compare with simulation results of routing delay. Simulation results show that the DQMR protocol outperforms multicast ad hoc on-demand distance vector routing protocol in terms of routing delay, control overhead, and PDR.Thong-Nhat TranToan-Van NguyenKyusung ShimDaniel Benevides Da CostaBeongku AnIEEEarticleCognitive mobile ad hoc networkscross-layerdeep Q-networkgame theoryQoS multicast routingElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 152841-152856 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Cognitive mobile ad hoc networks cross-layer deep Q-network game theory QoS multicast routing Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Cognitive mobile ad hoc networks cross-layer deep Q-network game theory QoS multicast routing Electrical engineering. Electronics. Nuclear engineering TK1-9971 Thong-Nhat Tran Toan-Van Nguyen Kyusung Shim Daniel Benevides Da Costa Beongku An A New Deep Q-Network Design for QoS Multicast Routing in Cognitive Radio MANETs
description	In this paper, we propose a new deep Q-network (DQN) design for quality-of-service (QoS) multicast routing (DQMR) protocol to establish efficient QoS multicast (EQM) trees in cognitive radio mobile ad hoc networks (CR-MANETs). An EQM tree is a shortest-path multicast tree with minimum end-to-end (E2E) cost (a combination of queuing size ratio and link stability) subject to QoS constraints such as queuing size ratio, link stability, number of hops, number of time slots and avoiding the licensed channel of primary users. Particularly, we propose an NP-complete optimization problem such that its feasible solution is an EQM tree. To address this problem, we design a new DQN model and a new game-based model to form EQM trees in real-time by offline training instead of online training as done in previous papers. Moreover, the DQMR protocol is also guaranteed to have high stability, low routing delay, low control overhead, and high packet delivery ratio (PDR). Furthermore, one more new contribution of the paper is that exact closed-form expressions for the E2E queuing delay of a multicast routing tree are also derived assuming random waypoint mobility and the reference point group mobility models to compare with simulation results of routing delay. Simulation results show that the DQMR protocol outperforms multicast ad hoc on-demand distance vector routing protocol in terms of routing delay, control overhead, and PDR.
format	article
author	Thong-Nhat Tran Toan-Van Nguyen Kyusung Shim Daniel Benevides Da Costa Beongku An
author_facet	Thong-Nhat Tran Toan-Van Nguyen Kyusung Shim Daniel Benevides Da Costa Beongku An
author_sort	Thong-Nhat Tran
title	A New Deep Q-Network Design for QoS Multicast Routing in Cognitive Radio MANETs
title_short	A New Deep Q-Network Design for QoS Multicast Routing in Cognitive Radio MANETs
title_full	A New Deep Q-Network Design for QoS Multicast Routing in Cognitive Radio MANETs
title_fullStr	A New Deep Q-Network Design for QoS Multicast Routing in Cognitive Radio MANETs
title_full_unstemmed	A New Deep Q-Network Design for QoS Multicast Routing in Cognitive Radio MANETs
title_sort	new deep q-network design for qos multicast routing in cognitive radio manets
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/f3477469621944988154e01a655445c7
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A New Deep Q-Network Design for QoS Multicast Routing in Cognitive Radio MANETs

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