A MAC Multi-channel Scheme Based on Learning-Automata for Clustered VANETs

Daknou, Emna; Tabbane, Nabil; Thaalbi, Mariem

doi:10.1109/aina.2018.00023

Cited by 5 publications

(5 citation statements)

References 14 publications

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“…LA algorithms do not need to know their usage scenarios or any knowledge about the target to be optimized is a major advantage [67]. In recent years, some works [21,67,68] have attempted to apply LA to solve various practical problems, e.g., optimizing congestionaware scheme and configuring the LA in the routing node.…”

Section: Reinforcement Learningmentioning

confidence: 99%

“…Some solutions are dedicated to rescue operations [8], forest fire monitoring and prevention [9]. Similarly, there are some works for underwater acoustic networks (UANs) [10][11][12], the Internet of things (IoT) [13][14][15][16], unmanned aerial vehicle (UAV) formations [17][18][19][20][21], vehicular ad hoc networks [22], flying ad hoc networks (FANET) [23][24][25], heterogeneous networks (HetNet) [26][27][28][29] and next-generation wireless communication [30][31][32]. In addition, there are some works aimed at security [33], robustness [34], energy saving [35,36], adaptability [37][38][39][40][40][41][42] and stability [43][44][45][46][47][48][49][50][51].…”

Section: Introductionmentioning

confidence: 99%

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Survey of Reinforcement-Learning-Based MAC Protocols for Wireless Ad Hoc Networks with a MAC Reference Model

Zheng

Jiang

Feng

et al. 2023

Entropy

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In this paper, we conduct a survey of the literature about reinforcement learning (RL)-based medium access control (MAC) protocols. As the scale of the wireless ad hoc network (WANET) increases, traditional MAC solutions are becoming obsolete. Dynamic topology, resource allocation, interference management, limited bandwidth and energy constraint are crucial problems needing resolution for designing modern WANET architectures. In order for future MAC protocols to overcome the current limitations in frequently changing WANETs, more intelligence need to be deployed to maintain efficient communications. After introducing some classic RL schemes, we investigate the existing state-of-the-art MAC protocols and related solutions for WANETs according to the MAC reference model and discuss how each proposed protocol works and the challenging issues on the related MAC model components. Finally, this paper discusses future research directions on how RL can be used to enable MAC protocols for high performance.

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Section: Reinforcement Learningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Survey of Reinforcement-Learning-Based MAC Protocols for Wireless Ad Hoc Networks with a MAC Reference Model

Zheng

Jiang

Feng

et al. 2023

Entropy

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“…Nodes are equipped with GPS, unlike other MACs that use CCH for safety applications and SCH for both safety and non-safety applications. The learning automaton model is implemented for the polling of cluster members to find out its parameter using the cluster head, with dynamic TDMA allocation of resources within the cluster [97].…”

Section: Lmmcmentioning

confidence: 99%

An Analysis on Contemporary MAC Layer Protocols in Vehicular Networks: State-of-the-Art and Future Directions

et al. 2021

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Traffic density around the globe is increasing on a day-to-day basis, resulting in more accidents, congestion, and pollution. The dynamic vehicular environment induces challenges in designing an efficient and reliable protocol for communication. Timely delivery of safety and non-safety messages is necessary for traffic congestion control and for avoiding road mishaps. For efficient resource sharing and optimized channel utilization, the media access control (MAC) protocol plays a vital role. An efficient MAC protocol design can provide fair channel access and can delay constraint safety message dissemination, improving road safety. This paper reviews the applications, characteristics, and challenges faced in the design of MAC protocols. A classification of the MAC protocol is presented based on contention mechanisms and channel access. The classification based on contention is oriented as contention-based, contention-free, and hybrid, whereas the classification based on channel access is categorized as distributed, centralized, cluster-based, cooperative, token-based, and random access. These are further sub-classified as single-channel and multi-channel, based on the type of channel resources they utilize. This paper gives an analysis of the objectives, mechanisms, advantages/disadvantages, and simulators used in specified protocols. Finally, the paper concludes with a discussion on the future scope and open challenges for improving the MAC protocol design.

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“…To overcome hidden terminal problems and merge collisions, an effective clustering technique is required. When using an allocated technique to assign a period allocation [4], two sorts of conflicts can occur: access collision and merge collision. Due to mobility, two vehicles that started more than two hops apart try to join a single period allocation at the same moment [5].…”

Section: Introductionmentioning

confidence: 99%

A Reliable Merging Link Scheme Using Weighted Markov Chain Model in Vehicular Ad Hoc Networks

Emmanuel

Isnin

Mohamad

2022

Sensors

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The vehicular ad hoc network (VANET) is a potential technology for intelligent transportation systems (ITS) that aims to improve safety by allowing vehicles to communicate quickly and reliably. The rates of merging collision and hidden terminal problems, as well as the problems of picking the best match cluster head (CH) in a merged cluster, may emerge when two or more clusters are merged in the design of a clustering and cluster management scheme. In this paper, we propose an enhanced cluster-based multi-access channel protocol (ECMA) for high-throughput and effective access channel transmissions while minimizing access delay and preventing collisions during cluster merging. We devised an aperiodic and acceptable merge cluster head selection (MCHS) algorithm for selecting the optimal merge cluster head (MCH) in centralized clusters where all nodes are one-hop nodes during the merging window. We also applied a weighted Markov chain mathematical model to improve accuracy while lowering ECMA channel data access transmission delay during the cluster merger window. We presented extensive simulation data to demonstrate the superiority of the suggested approach over existing state-of-the-arts. The implementation of a MCHS algorithm and a weight chain Markov model reveal that ECMA is distinct and more efficient by 64.20–69.49% in terms of average network throughput, end-to-end delay, and access transmission probability.

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A MAC Multi-channel Scheme Based on Learning-Automata for Clustered VANETs

Cited by 5 publications

References 14 publications

Survey of Reinforcement-Learning-Based MAC Protocols for Wireless Ad Hoc Networks with a MAC Reference Model

Survey of Reinforcement-Learning-Based MAC Protocols for Wireless Ad Hoc Networks with a MAC Reference Model

An Analysis on Contemporary MAC Layer Protocols in Vehicular Networks: State-of-the-Art and Future Directions

A Reliable Merging Link Scheme Using Weighted Markov Chain Model in Vehicular Ad Hoc Networks

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