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Game Theory-Based Network
Selection: Solutions and Challenges
Speaker: Kai-Wei Ping
Advisor: Prof Dr. Ho-Ting Wu
2013/05/20
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Outline
• Introduction
• Network selection problem
• Decision Making Process
 Decision Criteria
 Decision Making
• Game Theory
• Challenges in Game Theory and 4G
• Conclusions and future research directions
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Introduction
• Smart mobile computing devices have become
increasingly affordable and powerful.
• No single network technology will be equipped to
deal with this explosion of data, making the
coexistence of multiple radio access technologies
(RATs) a necessity
• The focus of this paper is to provide a
comprehensive survey of the current research on
game theory approaches in relation to network
selection solutions
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Network selection problem
• The next generation of wireless networks is
represented as a heterogeneous environment
with a number of overlapping RANs
• The user device faces the problem of selecting
from a number of RANs that differ in
technology, coverage, bandwidth, latency,
pricing scheme, etc., belonging to the same or
different service providers
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How
• How can an ordinary user, without any
background knowledge in wireless networks,
know which is the best deal for him?
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Network selection problem
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Standards which support Network
Selection
• IEEE 802.21 –
The standard enables the optimization of handover
between heterogeneous IEEE 802networks and
facilitates handover between IEEE 802 networks and
cellular networks
• Access Network Discovery and Selection Function
(ANDSF) –
Provides information about the neighbouring access
networks to the mobile device through Discovery
Information and assists the device in the handover
process through rule based network selection policies
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Decision Making Process
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Decision Criteria
• Network metrics –
includes information about the technical characteristics or
performance of the access networks
• Device related –
includes information about the end-users’terminal device
characteristics
• Application Requirements –
includes information about the requirements needed in order
to provide a certain service to the end user
• User Preferences –
includes information related to the end-users’ satisfaction
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Decision Making
• The Simple Additive Weighting Method (SAW) –
• The Technique for Order Preference by Similarity to
Ideal Solution (TOPSIS) –
• The Multiplicative Exponential Weighting
Method(MEW) –
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Decision Making
• The Elimination and Choice Expressing Reality
(ELECTRE)method –
concordance set (CSet) and discordance set (DSet) ,
Cthreshold and Dthreshold.
• Analytic Hierarchy Process (AHP) and Grey
Relational Analysis (GRA) –
 Analytic Hierarchy Process (AHP):
The idea behind AHP is to decompose a complicated problem
into a hierarchy of simple and easy to solve sub-problems
 Grey Relational Analysis (GRA):
The GRA method is used to rank candidate networks and select
the one which has the highest rank
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Game Theory
• Game theory is a mathematical tool used in
understanding and modelling competitive
situations which imply the interaction of
rational decision makers with mutual and
possibly conflicting interests.
• It was originally adopted in economics, in
order to model the competition between
companies.
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Glossary
• Player： A player is an agent who makes
decisions in a game.
• Strategy：In a game in strategic form, a strategy
is one of the given possible actions of a player
• Payoff： A payoff is a number, also called utility,
that reflects the desirability of an outcome to a
player, for whatever reason
• Rationality：A player is said to be rational if he
seeks to play in a manner which maximizes his
own payoff. It is often assumed that the
rationality of all players is common knowledge.
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Game Component
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Nash Equilibrium
• The combination of best strategies for each
player is known as equilibrium.
• When each player cannot benefit anymore by
changing his strategy while keeping the other
players’ strategies unchanged, then we say
hat the solution of the game represents Nash
Equilibrium.
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Pareto Optimality
• When the payoffs cannot be further enhanced
with any other strategy combination, the
game is said to have reached a Pareto Optimal
Nash Equilibrium
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Game Theoretic Models
1)
2)
3)
4)
5)
6)
7)
8)
9)
10)
11)
12)
Strategic Game: Prisoner’s Dilemma
Repeated Game
Bargaining Game
Trading Market
Auction Game
Cournot Game
Bankruptcy Game
Stackelberg Game / Leader-Follower Game
Bayesian Game
Coalition Game
Evolutionary Games
Mechanism Design
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Game Theory to Network Selection
Mapping
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Summary of surveyed approaches
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Summary of surveyed approaches
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Summary of surveyed approaches
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Case
• Source :
“4G Converged Environment: Modeling Network Selection as a Game”
• Game model :
Strategic Game
• Objective :
network selection - select the best network to satisfy a service request
•
•
•
•
•
Strategy set : the service requests
Payoff : Utility function
Parameter : delay, jitter
Resource : bandwidth
RAT : 4G system
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Example
• define the network
selection game as:
• N={1,2}, R={1,2,3,4,5,6},
S1={1,2,3,4,5,6} and
S2={1,2,3,4,5,6}.
•
is the value assigned
to network i for
choosing service
requestj
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Example
• Therefore, at the end of the game A1 = {6, 5, 4}
and A2 = {1, 2, 3}.
• The payoff to both networks is equal to 15;
• 6 each from the first round, 5 each from the
second and 4 each from the third
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Challenges in Game Theory and 4G
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Challenges in Game Theory and 4G
• Cooperative or Non-cooperative Approach –
The 4G environment aims to provide a combination
of network and terminal heterogeneity as well as
heterogeneous services
• Payoffs/Utility Functions –
The choice of payoff or utility function is another
challenge as it impacts on how the players will
choose their actions
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Challenges in Game Theory and 4G
• Multi-Operator and Multi-Technology –
when designing a cooperative or a non-cooperative
game, comes when considering a single or multiple
operators
• Pricing and Billing –
Multiple service providers , Multiple RATs
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Challenges in Game Theory and 4G
• Users’ Implication –
If not the best one to the customer, service providers
should know what each customer really needs and
where the real problem lies
• Energy Consumption –
 When considering the energy consumption of a
multi-interface mobile device, an important
aspect is the connectivity
 Solution : Cooperative Network protocol (CONET)
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Challenges in Game Theory and 4G
• Complexity and Real World Scenarios –
 In a real world scenario, considering the competitive
market, operators will not be willing to provide such
information without having a clear benefit from
doing so.
 Another important aspect when using game theory
and dealing with such a heterogeneous and complex
environment is the risk of users misbehaving, acting
selfishly by trying to obtain the maximum
performance over other users, leading to an overall
system performance degradation
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Conclusions and future research
directions
• This article aims to familiarize the readers with the
network selection concept and with the different game
theoretic approaches used in the literature to model
the network selection problem.
• As game theory is often used to study this interaction
between rational decision makers, it makes it
applicable in the area of network selection strategies.
• An important open issue is the impact of
computational complexity of the existing solutions
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References
• Ramona Trestian, Olga Ormond, and GabrielMiro Muntean, ” Game Theory-Based
Network Selection: Solutions and Challenges,”
in IEEE Communications Surveys & Tutorials,
vol. 14, no. 4, pp. 1212 - 1231, 2012.
• J. Antoniou and A. Pitsillides, ”4G Converged
Environment: Modeling Network Selection as
a Game,” in the 16th IST Mobile and Wireless
Communications Summit, 2007.
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