Stochastic Modeling of Single-Hop Cluster Stability in Vehicular Ad Hoc Networks

Abboud, Khadige; Zhuang, Weihua

doi:10.1109/tvt.2015.2396298

Cited by 54 publications

(29 citation statements)

References 26 publications

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“…The cluster member stability, usually represented by residence times of cluster, relates to cluster head selection mechanism and can be analyzed by stochastic mobility model [73]. For example, in order to improve the stability of cluster membership, lots of information, such as geographic position information of vehicles [71], the relative space position relations between vehicles and the center of the cluster [72], and the relative velocity between a vehicle with its neighboring vehicles [29], should be considered when selecting CHs.…”

Section: B Routing Protocolsmentioning

confidence: 99%

Vehicular Communications: A Network Layer Perspective

Peng

Liang

Shen

et al. 2019

IEEE Trans. Veh. Technol.

253

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Vehicular communications, referring to information exchange among vehicles, pedestrians, and infrastructures, have become very popular and been widely studied recently due to its great potential to support intelligent transportation and various safety applications. Via vehicular communications, manually driving vehicles and autonomous vehicles can collect useful information to improve traffic safety and support infotainment services. In this paper, we provide a comprehensive overview of recent research on enabling efficient vehicular communications from the network layer perspective. First, we introduce general applications and unique characteristics of vehicular networks and the corresponding classifications. Based on different driving patterns of vehicles, we divide vehicular networks into two categories, i.e., manually driving vehicular networks and automated driving vehicular networks, and then discuss the available communication techniques, network structures, routing protocols, and handoff strategies applied in these vehicular networks. Finally, we identify the challenges confronted by the current vehicular communications and present the corresponding research opportunities. Index TermsVehicular communications; manually driving vehicles; autonomous vehicles; routing protocols; handoff strategies; communication technologies. from the perspective of the physical layer in [1]. Via enabling vehicles to exchange information with other vehicles (i.e., vehicle-to-vehicle, V2V), pedestrians (i.e., vehicle-to-pedestrian, V2P), and infrastructures (i.e., vehicle-to-infrastructure, V2I), vehicular communications are expected to support a variety of applications, including intelligent transportation and safety applications [2], [3]. However, due to the high mobility and complicated communications environments, it is very challenging to provide efficient vehicular communications to satisfy the different requirements, especially, higher reliability and lower latency for sharing safety-related information.Manually driving vehicular networks (MDVNETs), referring to communications among vehicles with only manually driving patterns, are one of the main applications of vehicular communications and have been widely considered in the existing works [4]. MDVNETs can help manually driving vehicles to improve the traffic safety and provide infotainment services to drivers and passengers [3].Owing to the advances in sensor technologies, wireless communications, computational power, and intelligent control, a new driving pattern, named automated driving, is gradually applied in vehicles, and then autonomous vehicles (AVs) are generated and begin to be test-driven on the roads. According to a report from the National Highway Safety Administration (NHTSA) [5], passenger vehicles can be classified into five distinct levels of autonomy, as shown in Table I.Manually driving vehicles mentioned in this paper refer to the vehicles with level 0 autonomy while AVs refer to vehicles with level 4 autonomy. It is expected that no human actions o...

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Section: B Routing Protocolsmentioning

confidence: 99%

Vehicular Communications: A Network Layer Perspective

Peng

Liang

Shen

et al. 2019

IEEE Trans. Veh. Technol.

253

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show abstract

“…The impact of the relative vehicles velocities will result in two events affecting the cluster structure. These events are some vehicles leaving the cluster and/or some vehicles entering the cluster [19]. Relative speed level among vehicles can helps in keeping the vehicles in a cluster and reducing the probability of moving out of that cluster [20], [13], tried to create new reliable cluster.…”

Section: Vehicles Relative Velocitymentioning

confidence: 99%

A Novel Stable Clustering Approach based on Gaussian Distribution and Relative Velocity in VANETs

Talib¹,

Hassan²,

Hussin³

et al. 2018

ijacsa

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“…The continuous time Markov chain was used for modelling [18][19][20][21] in several papers. For this model, the special case of continuous time Markov chain, called birth-death process is used.…”

Section: Related Workmentioning

confidence: 99%

Analytical Modelling of Back-off Process of IEEE 802.11p using Continuous Markov Chain in VANETs

Priyanka¹,

Singh²,

Kumar³

2017

IJCA

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Recently, the IEEE has standardised the 802.11p protocol for Vehicular Ad hoc Network (VANET). The main medium access control mechanism (MAC) of IEEE 802.11p is known as Enhanced Distributed Channel Access (EDCA). EDCA uses a contention algorithm based on distributed coordination function to provide the access for traffic in each access category (AC). When the contention window reaches its maximum size, the contention window is reset to its minimum size when frames are transmitted successfully, or the associated retry counter is reached, and the frame is discarded. In this paper, propose an analytical model of the throughput for the IEEE 802.11p protocol is proposed using continuous time Markov chain (CTMC) with upper bound of drop limit. During transmission, some messages require RTS/CTS prior to transmitting data and others don't require it. Therefore, this idea along with the concept of drop limit is considered for modeling. A 3-D Markov chain is created to model the back off procedure for each access category. The analytical evaluation of the throughput for each access category of IEEE 802.11p EDCA has been given. The model is applicable for four access categories and the solution is given without including the computational complexity.

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Stochastic Modeling of Single-Hop Cluster Stability in Vehicular Ad Hoc Networks

Cited by 54 publications

References 26 publications

Vehicular Communications: A Network Layer Perspective

Vehicular Communications: A Network Layer Perspective

A Novel Stable Clustering Approach based on Gaussian Distribution and Relative Velocity in VANETs

Analytical Modelling of Back-off Process of IEEE 802.11p using Continuous Markov Chain in VANETs

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