Sogang University ICC Lab

Using Game Theory to Analyze Wireless Ad Hoc networks

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Outline

Ad-Hoc network Game theory Ad-Hoc + Game theory

Social optimal

Medium access layer

Network layerTransport layer

Physical layer

Layered approach

Future work

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Ad Hoc networks

• What are ad hoc networks- Multi-hop communication- Reduced need for any infrastructure- Dynamic topology- Distributed, interactive stations- Ease of deployment- Potentially more robust to attack

• Application of ad hoc networks- Military application- Disaster management- Impromptu communication between people

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Game Theory

• Game theory – a branch of mathematics used extensively in economics

• The study of mathematical models of conflict and cooperation between intelligent rational decision makers- (1991)

• Basic component: Game – A mathematical representation of an interactive decision situation

• Important concepts- Conflict and cooperation- Intelligent rational decision makers

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Basic component

• Strategic game – 3 basic components- A set of 2 or more players (N = {1,2,….n})- A set of actions for each player ( )- Utility function for every player ( )

• Nash equilibrium- An action vector is a Nash equilibrium if and - An action vector from which no player can benefit by

deviating unilaterally

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Prisoner’s dilemma

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Why game theory?

• De-centralized nature of nodes- Independently adapting its operation based on perceived

or measures statistics• Interactive decision makers

- Decision taken by one node affects and influences the other nodes

Available Adaptations

MANET Component Game Component

Action Set

Nodes in Network Player Set

Adaptation Algorithm

Decision Update Algorithm

Valuation Function(Preference Relations)

Utility Function

Learning Process

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Steps in application of game theory

• Develop a game theoretic model

- Solution of game’s Nash equilibrium yields information

about the steady state and convergence of the network

• Does a steady state exist?

- Uniqueness of Nash equilibrium

• Is it optimal?

• Do nodes converge to it?

• Is it stable?

• Does the steady state scale?

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Optimal equilibrium inducing mechanisms

• Credit exchange- Virtual currency

▪ Difficult to implement- Reputation

▪ Appropriate for denial of service attacks• Other schemes

- Generous Tit-for-tat▪ Node mimics the action of its peers▪ Slightly generous

- Watchdog mechanism▪ Specific to prevent malicious/selfish behavior in

routing• Presence of centralized referee

- Not a player but an overseer - Not a typical game theoretic scenario

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Physical and Medium access layers

• Power control

- Adjust transmit power levels

- Objective: To achieve a target signal-to-interference-to-

noise ratio

• Medium access

- Set the probability of packet transmission

- Objective: To maximize individual throughput

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Network layer (Research issues)• Previous work restricted to analyzing selfish node

behavior while forwarding of packets- Nodes decide on the proportion of packets/sessions to act

as a relay- Energy is the main constraint- “Selfishness is the only strategy that can naturally arise in

a single stage”

• Use of external incentive mechanisms to induce socially optimal equilibrium

• Shortcomings- Do not consider true ad hoc scenarios where nodes can

experience inherent trade-offs- Do not consider mobility and influence on entire network- Restrict the model to relaying packets

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Network layer (Current research)• Node participation

- Switch interfaces to a sleep state- Affects network operations

▪ Network partition ▪ Network congestion

- Individual losses▪ Loss of information for an ongoing session▪ Overhead involved in discovering location of other nodes on

waking up▪ Extra flow of route queries due to frequent topology changes

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Network layer (Other issues)

• Malicious node behavior degrades performance of

dynamic source routing protocol

• Classic routing

- Nodes decide on the amount of data to be sourced on

shared paths to minimize the cost involved

• Use of game theory – infant stage

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Transport layer

• Analyze congestion control algorithms for selfish nodes

- Objective: Determine the optimal congestion window

additive increase and multiplicative decrease parameters

- Current efforts restricted to traditional TCP congestion

control algorithms for wired networks

• Ad hoc networks

- Incorporate the characteristics of the wireless medium in

the congestion control game

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Summary

• Game theory offers a promising set of tools to analytically model ad hoc networks

• Game theory can be used- Analysis of ad hoc networks- Design of incentive mechanisms

• Past research concentrated on wired/cellular networks

• Design of robust protocols to deal with selfish behavior

• Not completely realistic : Difficult to obtain social optimum in a distributed environment of rational entities

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Future Work

• Currently developing a model for node participation in an ad hoc network

• Analyze the model using game theoretic techniques and determine the optimal in the ad hoc network

• Apply the node participation model to a well known routing protocol and study the effect of varying level of node participation

• Incorporate mobility in the game theoretic model