A game theoretical approach to model vehicular broadcast communication

Muhammad Jafer; M. Arif Khan; Sabih Rehman; Tanveer A. Zia

doi:10.1109/VTC2021-Fall52928.2021.9625528

A game theoretical approach to model vehicular broadcast communication

Muhammad Jafer, M. Arif Khan, Sabih Rehman, Tanveer A. Zia

Naif Arab University for Security Sciences

Research output: Book chapter/Published conference paper › Conference paper › peer-review

Abstract

A vehicular ad-hoc network consists of multiple local networks due to the limited communication range of Onboard Processing Unit utilised by participating vehicles. Therefore, multiple re-transmission attempts by relay vehicles are required to propagate an original information packet. However, these necessary re-transmissions cause Broadcast Storm Problem (BSP) which can in-turn create network congestions. This paper addresses the issues associated with BSP by proposing an Optimised Relay Vehicle Selection (ORVS) mechanism. To devise the strategy for an ORVS mechanism, an Evolutionary Game (EG) strategy is utilised that consists of a novel payoff function. In addition to this, we also propose a (BG) to simulate a VANET environment, which is implemented using Python, for collection of results. The numerical results obtained by the proposed EG are compared with the existing techniques, which show better performance by the ORVS mechanisms produced by the game theoretical approaches.

Original language	English
Title of host publication	2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall)
Publisher	IEEE
Number of pages	6
ISBN (Electronic)	9781665413688
ISBN (Print)	9781665413695
DOIs	https://doi.org/10.1109/VTC2021-Fall52928.2021.9625528
Publication status	Published - 10 Dec 2021
Event	2021 IEEE 94th Vehicular Technology Conference: VTA2021-Fall - Online Duration: 27 Sept 2021 → 28 Oct 2021 https://events.vtsociety.org/vtc2021-fall/ https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9625311 (Final program) https://ieeexplore.ieee.org/xpl/conhome/9624467/proceeding (Conference proceedings)

Publication series

Name
Publisher	IEEE
ISSN (Print)	1090-3038
ISSN (Electronic)	2577-2465

Conference

Conference	2021 IEEE 94th Vehicular Technology Conference
Period	27/09/21 → 28/10/21
Other	The 2021 IEEE 94th Vehicular Technology Conference: VTC2021-Fall will be held as a virtual conference, 27 September - 28 October 2021. This semi-annual flagship conference of IEEE Vehicular Technology Society will bring together individuals from academia, government, and industry to discuss and exchange ideas in the fields of wireless, mobile, and vehicular technology. IEEE VTC2021-Fall will feature world-class plenary speakers, tutorials, technical as well as application sessions, and an innovative Industry Track, which will feature panels and presentations with industry leaders sharing their perspectives on the latest technologies.
Internet address	https://events.vtsociety.org/vtc2021-fall/ https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9625311 (Final program) https://ieeexplore.ieee.org/xpl/conhome/9624467/proceeding (Conference proceedings)

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10.1109/VTC2021-Fall52928.2021.9625528

Cite this

@inproceedings{e41e0b7439694a538e813e9ff3c93c33,

title = "A game theoretical approach to model vehicular broadcast communication",

abstract = "A vehicular ad-hoc network consists of multiple local networks due to the limited communication range of Onboard Processing Unit utilised by participating vehicles. Therefore, multiple re-transmission attempts by relay vehicles are required to propagate an original information packet. However, these necessary re-transmissions cause Broadcast Storm Problem (BSP) which can in-turn create network congestions. This paper addresses the issues associated with BSP by proposing an Optimised Relay Vehicle Selection (ORVS) mechanism. To devise the strategy for an ORVS mechanism, an Evolutionary Game (EG) strategy is utilised that consists of a novel payoff function. In addition to this, we also propose a (BG) to simulate a VANET environment, which is implemented using Python, for collection of results. The numerical results obtained by the proposed EG are compared with the existing techniques, which show better performance by the ORVS mechanisms produced by the game theoretical approaches.",

keywords = "VANET's, Broadcasting, Evolutionary game, Bayesian game, Nework coverage",

author = "Muhammad Jafer and Khan, {M. Arif} and Sabih Rehman and Zia, {Tanveer A.}",

note = "Includes bibliographical references.; 2021 IEEE 94th Vehicular Technology Conference : VTA2021-Fall ; Conference date: 27-09-2021 Through 28-10-2021",

year = "2021",

month = dec,

day = "10",

doi = "10.1109/VTC2021-Fall52928.2021.9625528",

language = "English",

isbn = "9781665413695",

publisher = "IEEE",

booktitle = "2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall)",

url = "https://events.vtsociety.org/vtc2021-fall/, https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9625311, https://ieeexplore.ieee.org/xpl/conhome/9624467/proceeding",

}

TY - GEN

T1 - A game theoretical approach to model vehicular broadcast communication

AU - Jafer, Muhammad

AU - Khan, M. Arif

AU - Rehman, Sabih

AU - Zia, Tanveer A.

N1 - Includes bibliographical references.

PY - 2021/12/10

Y1 - 2021/12/10

N2 - A vehicular ad-hoc network consists of multiple local networks due to the limited communication range of Onboard Processing Unit utilised by participating vehicles. Therefore, multiple re-transmission attempts by relay vehicles are required to propagate an original information packet. However, these necessary re-transmissions cause Broadcast Storm Problem (BSP) which can in-turn create network congestions. This paper addresses the issues associated with BSP by proposing an Optimised Relay Vehicle Selection (ORVS) mechanism. To devise the strategy for an ORVS mechanism, an Evolutionary Game (EG) strategy is utilised that consists of a novel payoff function. In addition to this, we also propose a (BG) to simulate a VANET environment, which is implemented using Python, for collection of results. The numerical results obtained by the proposed EG are compared with the existing techniques, which show better performance by the ORVS mechanisms produced by the game theoretical approaches.

AB - A vehicular ad-hoc network consists of multiple local networks due to the limited communication range of Onboard Processing Unit utilised by participating vehicles. Therefore, multiple re-transmission attempts by relay vehicles are required to propagate an original information packet. However, these necessary re-transmissions cause Broadcast Storm Problem (BSP) which can in-turn create network congestions. This paper addresses the issues associated with BSP by proposing an Optimised Relay Vehicle Selection (ORVS) mechanism. To devise the strategy for an ORVS mechanism, an Evolutionary Game (EG) strategy is utilised that consists of a novel payoff function. In addition to this, we also propose a (BG) to simulate a VANET environment, which is implemented using Python, for collection of results. The numerical results obtained by the proposed EG are compared with the existing techniques, which show better performance by the ORVS mechanisms produced by the game theoretical approaches.

KW - VANET's

KW - Broadcasting

KW - Evolutionary game

KW - Bayesian game

KW - Nework coverage

U2 - 10.1109/VTC2021-Fall52928.2021.9625528

DO - 10.1109/VTC2021-Fall52928.2021.9625528

M3 - Conference paper

SN - 9781665413695

BT - 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall)

PB - IEEE

T2 - 2021 IEEE 94th Vehicular Technology Conference

Y2 - 27 September 2021 through 28 October 2021

ER -

A game theoretical approach to model vehicular broadcast communication

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