A Fast Cloud-Based Network Selection Scheme Using Coalition Formation Games in Vehicular Networks

Xu, Ke; Wang, Kuang-Ching; Amin, Rahul; Martin, Jim; Izard, Ryan

doi:10.1109/tvt.2014.2379953

Cited by 48 publications

(21 citation statements)

References 27 publications

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“…These two contributions [72][71] could have convergence time issues due to a exponentially increasing complexity in the algorithm to form the coalitions of vehicles when the number of vehicles is relatively high. Alternatively, in [188] the algorithm to form coalitions only requires a single iteration, making it a scalable solution in terms of the number of vehicles, each of which is searching for the best access network. A limitation of this proposal is that at any given time, a vehicle can use only a single network interface.…”

Section: Vehicular Networkmentioning

confidence: 99%

Game Theory for Multi-Access Edge Computing: Survey, Use Cases, and Future Trends

Moura

Hutchison

2019

IEEE Commun. Surv. Tutorials

165

106

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Game Theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming Multi-Access Edge Computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as Quality of Experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely: rational vs. evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse trade-offs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios.

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Section: Vehicular Networkmentioning

confidence: 99%

Game Theory for Multi-Access Edge Computing: Survey, Use Cases, and Future Trends

Moura

Hutchison

2019

IEEE Commun. Surv. Tutorials

165

106

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“…Therefore, Liu et al [34] reported two decentralized data offloading mechanisms: multi-item auction (MIA)-based and congestion game (COG)-based. Xu et al [35] proposed a fast cloud-based network selection scheme for vehicular networks. Vehicles select the optimal access networks via a coalition formation game approach.…”

Section: Incentive Schemes For Data Offloadingmentioning

confidence: 99%

“…Vehicles select the optimal access networks via a coalition formation game approach. However, in [34] and [35], the mobility of vehicles is not considered. In contrast to the above incentive schemes, Dua et al [36] developed a game-theory-based algorithm for selecting the optimal vehicle onto which to offload data from RSUs that considers the connectivity, density of vehicles, distance, speed and angle of movement.…”

Section: Incentive Schemes For Data Offloadingmentioning

confidence: 99%

Stackelberg-Game-Based Mechanism for Opportunistic Data Offloading Using Moving Vehicles

et al. 2019

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Data offloading through vehicular ad hoc networks (VANETs) is one of the most promising methods for overcoming the overload problem in cellular networks. As data delivery by service providers consumes resources such as bandwidth, storage and power, the incentive scheme with the optimal pricing strategy must be identified. In the literature, most incentive schemes focus on offloading through fixed nodes, such as roadside units (RSUs). It remains very challenging to motivate a moving vehicle to help other users deliver their data due to the high mobility of vehicles. Game theory is a widely adopted method for analyzing pricing issues in wireless networks. Therefore, this paper proposes an optimal pricing strategy that uses the Stackelberg game to model the interaction between a service provider and a service requester. Then, the Stackelberg equilibrium is derived under the corresponding conditions. Next, an algorithm is proposed for selecting the service provider that offers the lowest price based on the results of the Stackelberg equilibrium. Finally, the simulation results demonstrate that the proposed algorithm can effectively reduce the downloading time of a task while maximizing the utilities of both the service provider and the requester.

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“…Bankruptcy game model, a cooperative, network vs network game model, is used, where players are the available network and the strategy is the coalition formation of the available network to provide resources to the user and the payoff is calculated using characteristic function for each coalition formed . Cloud‐based network selection using coalition formation game is used to balance system throughput and fairness with built‐in utility division rule of the framework. The algorithm efficiency showed 8‐time enhancement over a conventional coalition formation algorithm.…”

Section: Related Workmentioning

confidence: 99%

Improved network selection for multimedia applications

Munjal

Singh

2016

Trans. Emerging Tel. Tech.

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Fifth generation mobile networks are being developed to compensate the explosive growth of data traffic and shortage of spectrum. Fifth generation networks consist of multi‐tier heterogeneous network in which multi cells and multi networks are involved. The heterogeneity of different classes of base station improves spectral efficiency and provides flexible coverage area. Hence, in the heterogeneous network environment, deciding to which one mobile should connect is called network selection problem. In this paper, network selection problem in heterogeneous network is simulated by multi attribute decision making algorithm, game theory, and prospect theory. Prospect theory is new in the field of network selection. The weights for different network attributes are computed by analytical hierarchical process, standard deviation, and entropy method. The 4 different applications, i.e., video, voice, web browsing, and email transfer are considered for which available bandwidth, packet jitter, packet loss, and cost per byte are taken as most important attributes, respectively. The weights for different applications are calculated by analytical hierarchical process method. The selection is done in environment composed of heterogeneous networks such as Wi‐Fi, WiMAX, WLAN, LTE, UMTS, and GPRS. So different networks are selected for different applications because only 1 network cannot fulfill the requirement of the all applications. The performance of different methods is shown in relative standard deviation and accuracy. Prospect theory gives the maximum values of relative standard deviation and accuracy.

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A Fast Cloud-Based Network Selection Scheme Using Coalition Formation Games in Vehicular Networks

Cited by 48 publications

References 27 publications

Game Theory for Multi-Access Edge Computing: Survey, Use Cases, and Future Trends

Game Theory for Multi-Access Edge Computing: Survey, Use Cases, and Future Trends

Stackelberg-Game-Based Mechanism for Opportunistic Data Offloading Using Moving Vehicles

Improved network selection for multimedia applications

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