BMCGM: A Behavior Economics-Based Message Transmission Cooperation Guarantee Mechanism in Vehicular Ad-hoc NETworks

Liu, Jiaqi; Zhong, Nan; Li, Deng; Liu, Hui

doi:10.3390/s18103316

Cited by 6 publications

(5 citation statements)

References 51 publications

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“…Dubey et al developed an incentive-based protocol based on coalition game theory, in which vehicles have an incentive to forward data as members of a coalition to improve reliability and fairness in VANETs [8]. Liu et al designed an incentive system that uses the reciprocal altruistic factor to reconstruct the utility function of vehicles [9]. They demonstrated that their system can reduce message transmission delay by up to 30% compared to other cooperative transmission mechanisms.…”

Section: Related Workmentioning

confidence: 99%

Ecological Dynamics and Evolution of Cooperation in Vehicular Ad Hoc Networks

Sartakhti

Ghajar

2023

Telecom

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In Vehicular Ad Hoc Networks (VANETs), promoting cooperative behavior is a challenging problem for mechanism designers. Cooperative actions, such as disseminating data, can seem at odds with rationality and may benefit other vehicles at a cost to oneself. Without additional mechanisms, it is expected that cooperative behavior in the population will decrease and eventually disappear. Classical game theoretical models for cooperation, such as the public goods game, predict this outcome, but they assume fixed population sizes and overlook the ecological dynamics of the interacting vehicles. In this paper, we propose an evolutionary public goods game that incorporates VANET ecological dynamics and offers new insights for promoting cooperation. Our model considers free spaces, population density, departure rates of vehicles, and randomly composed groups for each data sender. Theoretical analysis and simulation results show that higher population densities and departure rates, due to minimum differences between pay-offs of vehicles, promote cooperative behavior. This feedback between ecological dynamics and evolutionary game dynamics leads to interesting results. Our proposed model demonstrates a new extension of evolutionary dynamics to vehicles of varying densities. We show that it is possible to promote cooperation in VANETs without the need for any supporting mechanisms. Future research can investigate the potential for using this model in practical settings.

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Section: Related Workmentioning

confidence: 99%

Ecological Dynamics and Evolution of Cooperation in Vehicular Ad Hoc Networks

Sartakhti

Ghajar

2023

Telecom

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“…Loss aversion in behavioral economics [33] means that people are more averse to lose than gain. Behavioral economics has been widely used in the computer field [34][35][36]. In mobile crowdsourcing [34], loss aversion is used to redefine the utility function of nodes.…”

Section: Incentive Mechanism Of Vanetsmentioning

confidence: 99%

“…In mobile crowdsourcing [34], loss aversion is used to redefine the utility function of nodes. Reference [35] used reciprocal altruism in behavioral economics to promote message delivery in the Internet of Vehicles. Reference [36] used reciprocal altruism to improve the cooperation rate of social networks and to promote the spread of cooperation behaviors.…”

Section: Incentive Mechanism Of Vanetsmentioning

confidence: 99%

Cooperation Promotion from the Perspective of Behavioral Economics: An Incentive Mechanism Based on Loss Aversion in Vehicular Ad-Hoc Networks

Liu

Huang

et al. 2021

Electronics

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As a special mobile ad-hoc network, Vehicular Ad-hoc Networks (VANETs) have the characteristics of high-speed movement, frequent topology changes, multi-hop routing, a lack of energy, storage space limitations, and the possible selfishness of the nodes. These characteristics bring challenges to the design of the incentive mechanism in VANETs. In the current research on the incentive mechanism of VANETs, the mainstream is the reward-based incentive mechanism. Most of these mechanisms are designed based on the expected utility theory of traditional economics and assume that the positive and negative effects produced by an equal amount of gain and loss are equal in absolute value. However, the theory of loss aversion points out that the above effects are not equal. Moreover, this will lead to a deviation between the final decision-making behavior of nodes and the actual optimal situation. Therefore, this paper proposed a Loss-Aversion-based Incentive Mechanism (LAIM) to promote the comprehensive perception and sharing of information in the VANETs. This paper designs the incentive threshold and the threshold factor to motivate vehicle nodes to cooperate. Furthermore, based on the number of messages that the nodes face, the utility function of nodes is redesigned to correct the assumption that a gain and a loss of an equal amount could offset each other in traditional economics. The simulation results show that compared with the traditional incentive mechanism, the LAIM can increase the average utility of nodes by more than 34.35%, which promotes the cooperation of nodes.

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“…Elite Individuals Assist in Cross-Operation. This paper is inspired by [34] to design a new crossover algorithm assisted by elite individuals. Reference [34] uses the same elite individuals to cross-operate with crossover individuals.…”

Section: Algorithm 1: Attribute Reduction Based On the Genetic Algorimentioning

confidence: 99%

“…This paper is inspired by [34] to design a new crossover algorithm assisted by elite individuals. Reference [34] uses the same elite individuals to cross-operate with crossover individuals. This kind of operation can quickly lead the population towards elite individuals, but it also greatly reduces population diversity.…”

Section: Algorithm 1: Attribute Reduction Based On the Genetic Algorimentioning

confidence: 99%

Attribute Reduction Based on Genetic Algorithm for the Coevolution of Meteorological Data in the Industrial Internet of Things

Cheng

Zheng

Wang

et al. 2019

Wireless Communications and Mobile Computing

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Due to the problem of attribute redundancy in meteorological data from the Industrial Internet of Things (IIoT) and the slow efficiency of existing attribute reduction algorithms, attribute reduction based on a genetic algorithm for the coevolution of meteorological data was proposed. The evolutionary population was divided into two subpopulations: one subpopulation used elite individuals to assist crossover operations to increase the convergence speed of the algorithm, and the other subpopulation balanced the population diversity in the evolutionary process by introducing a random population; these two subpopulations completed the evolutionary operations together. With the TSDPSO-AR algorithm and ARAGA algorithm, the attribute reduction operation for precipitation in meteorological data was performed. The results showed that the proposed algorithm maintained the diversity of the population during evolution, improved the reduction performance, and simplified the information system.

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BMCGM: A Behavior Economics-Based Message Transmission Cooperation Guarantee Mechanism in Vehicular Ad-hoc NETworks

Cited by 6 publications

References 51 publications

Ecological Dynamics and Evolution of Cooperation in Vehicular Ad Hoc Networks

Ecological Dynamics and Evolution of Cooperation in Vehicular Ad Hoc Networks

Cooperation Promotion from the Perspective of Behavioral Economics: An Incentive Mechanism Based on Loss Aversion in Vehicular Ad-Hoc Networks

Attribute Reduction Based on Genetic Algorithm for the Coevolution of Meteorological Data in the Industrial Internet of Things

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