Elsevier

Physical Communication

Volume 4, Issue 3, September 2011, Pages 156-171
Physical Communication

Full length article
Reputation-based network selection mechanism using game theory

https://doi.org/10.1016/j.phycom.2011.06.004Get rights and content

Abstract

Current and future wireless environments are based on the coexistence of multiple networks supported by various access technologies deployed by different operators. As wireless network deployments increase, their usage is also experiencing a significant growth. In this heterogeneous multi-technology multi-application multi-terminal multi-user environment users will be able to freely connect to any of the available access technologies. Network selection mechanisms will be required in order to keep mobile users “always best connected” anywhere and anytime. In such a heterogeneous environment, game theory techniques can be adopted in order to understand and model competitive or cooperative scenarios between rational decision makers. In this work we propose a theoretical framework for combining reputation-based systems, game theory and network selection mechanism. We define a network reputation factor which reflects the network’s previous behaviour in assuring service guarantees to the user. Using the repeated Prisoner’s Dilemma game, we model the user–network interaction as a cooperative game and we show that by defining incentives for cooperation and disincentives against defecting on service guarantees, repeated interaction sustains cooperation.

Introduction

The next generation of wireless networks is already making its way into our daily lives. Because of the ease of use, affordability, and power of the new mobile devices and the wide range of new mobile applications, mobile users’ demands are increasing. According to Cisco [1], the compound annual growth of mobile data traffic is approximately 108%, and expected to reach 3.6 exabytes per month by 2014. More than 90% of the entire mobile broadband traffic is generated by laptops, netbooks, and smartphones. The advances in mobile devices enable people to connect to the Internet from anywhere at any time while on the move (e.g. on foot, in the car, on the bus, stuck in traffic, etc.) or stationary (e.g., at home/office/airport/coffee bars, etc.). Moreover, with the popularity of video-sharing websites like: YouTube, social networks (Twitter, Facebook, Linkedin, MySpace, etc.), mobile TV, entertainment services, etc., there is an exponential growth in video traffic. According to [1], video traffic is expected to reach 66% of the overall wireless data traffic by 2014.

In order to cope with this explosion in data traffic, network operators have started to deploy different radio access technologies in overlapping areas, such as: WLAN, WiMAX, UMTS, and the most recent, LTE. In this way they can accommodate more and more subscribers increasing their revenue.

The coexistence of multiple access technologies deployed by different operators has come to play a very important role, seeking to offer always best connectivity [2] to the Internet for mobile users. Mobile users want to be on the best value network that best satisfies their preferences for their current application(s), while the network operators want to maximize revenue by efficiently using their networks to satisfy and retain the most users possible. Challenges for the operators include network optimization especially for video traffic, if it represents two-thirds of the overall wireless traffic. Uninterrupted, continuous, and smooth video streaming, minimal delay, jitter, and packet loss, must be provided in order to avoid degradation in video quality and user experience. The main challenge for the users’ multi-mode terminal is to be on the best available radio access network (RAN). The network selection decision is a complex one, with the challenge of trading-off different decision criteria, (e.g. service class type, user’s preferences, mobile device being used, battery level, network load, time of day, price, etc.) this is further complicated by the combination of static and dynamic information involved, the accuracy of the information available, and the effort in collecting all of this information with a battery, memory, and processor limited device. This selection decision needs to be made once for connection initiation and subsequently as part of all handover decisions.

Game theory is a mathematical tool aimed at understanding and modelling competitive situations which imply the interaction of rational decision makers with mutual and possibly conflicting interests. In this article we extended our previous work presented in [3] and propose a novel reputation-based network selection mechanism. In [3] we proposed a power-friendly access network selection strategy which selects the least power consuming network in order to avoid the mobile device running out of battery. In this work we focus on the user–network interaction and we define a network reputation factor obtained as a result of the repeated cooperative game. The network reputation factor is integrated then in the network selection decision. To our knowledge no other work combines reputation-based systems with game theory in order to build a reputation-based network selection mechanism.

We start in Section 2 by providing a classification of game theory approaches which focus on resource allocation and network selection. The related works in the area of reputation-based systems are also discussed. In Section 3 we propose a combined network selection and game theory solution. In Section 4 a two-player repeated cooperative game is formulated using the model of repeated Prisoner’s Dilemma and the main components of the game are described. Using the cooperative approach, it is assumed that players will cooperate in order to maximize their payoffs. In a realistic scenario, players may choose to cheat or to behave selfishly by seeking to optimize their own payoffs. In Section 5 we analyse the equilibrium of the game. We show that, by defining incentives for cooperation and disincentives against cheating or selfish behaviour, repeated interaction leads to cooperation. Considering the heterogeneous scenario where users have a pool of choices with different RANs (Radio Access Networks) belonging to different operators and users are able to freely choose between them without any contractual agreement. In this situation there is a need for an assurance of service guarantees from both parties. The repeated user–network interaction can be seen as an ongoing relationship in which by using cooperative game theory we demonstrate that we can sustain cooperation without a contract. Section 6 details the computation of the network reputation factor and in Section 7 we present the numerical analysis and simulation results. Conclusions and future work are detailed in Section 8.

Section snippets

Related work

One of the first published works on network selection strategies was in 1999 by Wang et al. [4] in which they described a policy-enabled network selection function that uses a cost function defined as the sum of a weighted normalized form of three parameters: bandwidth, power consumption and price. The network with the lowest value for the cost function is chosen as the target network. This cost or score function can be formally classified as a Simple Additive Weighted (SAW) method. Other

System architecture

In this work we propose a reputation-based network selection mechanism based on an extended version of the IEEE 802.21 model [3]. The proposed mechanism makes use of the repeated cooperative game from Game Theory in order to model the user–network interaction and to compute the reputation of the network. Fig. 2 illustrates the system architecture of the proposed network selection mechanism.

The role of the Network Detection Manager is to scan the surrounding area and to provide a list of the

Two-player repeated cooperative game formulation and components

In order to study the interaction between the user and the network, we make use of game theory and formulate the problem as a cooperative repeated Prisoner’s Dilemma game. The user and the network cooperate in order to achieve Nash equilibrium. The outcome of the game seeks to reach both the user and the network satisfaction. The game can be defined as follows:

  • Players: The players in this game are the user and the network.

  • Strategies: Following the model of the repeated Prisoner’s Dilemma game,

Analysis of equilibrium

After the network selection decision takes place, and the target network is selected, the two-player repeated cooperative game starts. We assume that the game starts with the network’s Cooperate strategy. If the user’s response will be Cooperate, then the network will switch to playing GRIM. Even though the network’s strategy is Cooperate, it might happen that the user perceives degradation in the quality of service. This is because of the wireless environment where connections are prone to

Network reputation factor

In our work, in order to strengthen the cooperation between users and networks by keeping track of past behaviour, we define a network reputation factor, φ which is considered in the network selection decision. φ is computed based on the user’s past interactions with the network. We assume that at the first contact between user and network, φ=1, meaning that the network reputation factor will not have any impact on the selection as there is no history between the user and the network.

Assuming a

Impact of different strategies on the payoffs

In this section we examine the impact of different strategies and payoffs on the user–network interaction. In order to do this we implemented an analytical model of the repeated game in Matlab. There are three strategies for the network: GRIM—the network cooperates as long as the user cooperates, Always Defect—the network defects in each round, and Random Behaviour—there is a random chance for the network to defect of to cooperate. On the other side, the user can make use of four strategies:

Conclusions and future work

In this paper we study the interaction between user and network and we propose a novel reputation-based network selection mechanism. The mechanism combines the reputation-based systems and game theory in order to strengthen the cooperation between users and networks. We model the interaction between user and network as a two-player cooperative game using the model of repeated Prisoner’s Dilemma game. We define the network reputation factor based on the output of the repeated game, in order to

Acknowledgements

The support of Enterprise Ireland—Proof of Concept, Science Foundation Ireland—Research Frontiers Programme, and Dublin City University is gratefully acknowledged.

Ramona Trestian is a Ph.D. researcher with the Performance Engineering Laboratory, School of Electronic Engineering, Dublin City University, Ireland. She was awarded the B.Eng. degree in Telecommunications from the Electronics, Telecommunications and the Technology of Information Department, Technical University of Cluj-Napoca, Romania in 2007. Her research interests include wireless mobile networks, multimedia streaming over wireless access networks as well as handover and network selection

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    Ramona Trestian is a Ph.D. researcher with the Performance Engineering Laboratory, School of Electronic Engineering, Dublin City University, Ireland. She was awarded the B.Eng. degree in Telecommunications from the Electronics, Telecommunications and the Technology of Information Department, Technical University of Cluj-Napoca, Romania in 2007. Her research interests include wireless mobile networks, multimedia streaming over wireless access networks as well as handover and network selection strategies. She is student member of IEEE and The Rince Institute, Ireland.

    Olga Ormond is a Research Officer with the Network Innovations Centre in The Rince Institute, Dublin City University. Her research interests are in the area of next generation networks in particular heterogeneous wireless networks. She has published in prestigious international conferences, and is a reviewer for international journals and conferences and a member of IEEE. In 2007 she graduated from University College Dublin (UCD) with a Ph.D. A DCU graduate with a B.Eng in Telecommunications, Dr. Ormond previously worked for Ericsson Systems Expertise Ltd and Broadcom Éireann Research Ltd.

    Gabriel-Miro Muntean is a Lecturer with the School of Electronic Engineering, Dublin City University (DCU), Ireland, where he obtained his Ph.D. degree in 2003 for research on quality-oriented adaptive multimedia streaming over wired networks. He was awarded the B.Eng. and M.Sc. degrees in Software Engineering from the Computer Science Department, “Politehnica” University of Timisoara, Romania in 1996 and 1997 respectively. Dr. Muntean is Co-director of the DCU Performance Engineering Laboratory research group and Director of the Network Innovations Centre, part of the RINCE Research Institute Ireland. His research interests include quality-oriented and performance-related issues of adaptive multimedia delivery, performance of wired and wireless communications, energy-aware networking and personalised e-learning. Dr. Muntean has published over 100 papers in prestigious international journals and conferences, has authored a book and six book chapters and has edited two other books. Dr. Muntean is an Associate Editor of the IEEE Transactions on Broadcasting and reviewer for other important international journals, conferences and funding agencies. He is a member of IEEE, and IEEE Broadcast Technology Society.

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