non-cooperative behavior in wireless networks márk félegyházi (epfl) may 2007
Post on 19-Dec-2015
216 views
TRANSCRIPT
Non-Cooperative Behavior
in Wireless Networks
Márk Félegyházi (EPFL)
May 2007
May 2007 Márk Félegyházi (EPFL) 2
Prospective wireless networks
Relaxing spectrum licensing: ► small network operators in unlicensed bands
– inexpensive access points– flexible deployment
► community and ad hoc networks– no authority– peer-to-peer network operation
► cognitive radio– restricted operation in any frequency band– no interference with licensed (primary) users– adaptive behavior
May 2007 Márk Félegyházi (EPFL) 3
Motivation
► more complexity at the network edges► decentralization► ease of programming for wireless devices► rational users
► more adaptive wireless devices► potential selfish behavior of devices
TR
EN
DS
OU
TC
OM
E
What is the effect of selfish behavior in wireless networks?
May 2007 Márk Félegyházi (EPFL) 4
Related work (1/2)► Peer-to-peer networks
– free-riding [Golle et al. 2001, Feldman et al. 2007]– trust modeling [Aberer et al. 2006]
► Wired networks– congestion pricing [Korilis et al. 1995, Korilis and Orda 1999, Johari and
Tsitsiklis 2004]– bandwidth allocation [Yaïche et al. 2000]– coexistence of service providers [Shakkottai and Srikant 2005/2006, He
and Walrand 2006]► Wireless networks
– power control [Goodman and Mandayam 2001, Alpcan et al. 2002, Xiao et al. 2003]
– resource/bandwidth allocation [Marbach and Berry 2002, Qui and Marbach 2003]
– medium access [MacKenzie and Wicker 2003, Yuen and Marbach 2005, Čagalj et al. 2005]
– Wi-Fi pricing [Musacchio and Walrand 2004/2006]
May 2007 Márk Félegyházi (EPFL) 5
http://secowinet.epfl.ch
Related work (2/2)
1. Existing networks
2. Upcoming networks
3. Trust
4. Naming and addressing
5. Security associations
6. Secure neighbor discovery
7. Secure routing
8. Privacy protection
10. Selfishness in PKT FWing
11. Operators in shared spectrum
12. Behavior enforcement
Appendix A:Security and crypto
Appendix B:Game theory
Security Cooperation
9. Selfishness at the MAC layer
May 2007 Márk Félegyházi (EPFL) 6
Summary of my research
► Ch 1: A tutorial on game theory► Ch. 2: Multi-radio channel allocation in wireless networks► Ch. 3: Packet forwarding in static ad-hoc networks► Ch. 4: Packet forwarding in dynamic ad-hoc networks► Ch. 5: Packet forwarding in multi-domain sensor networks► Ch. 6: Cellular operators in a shared spectrum► Ch. 7: Border games in cellular networks
Part II: Non-cooperative users
Part III: Non-cooperative network operators
Part I: Introduction to game theory
Introduction to Game Theory
May 2007 Márk Félegyházi (EPFL) 8
The channel allocation (CA) game
► two channels: c1 and c2 – total available throughput: and
► two devices: p1 and p2
► throughput is fairly shared► users of the devices are rational
► Channel Allocation (CA) game: GCA = (, , )– – players: p1 and p2
– – strategies: choosing the channels• and
– – payoff functions: received throughputs• and
13t
c
c1 c2
f1 f2 f3
22t
c
11 pu 22 pu
1 1 2{ , }s c c 2 1 2{ , }s c c is S strategy of player i
iu U payoff of player i1 2( , )s s s strategy profile
May 2007 Márk Félegyházi (EPFL) 9
Strategic form
► the CA game in strategic form
p2
c1 c2
p1
c1 1.5,1.5 3,2
c2 2,3 1,1
13t
c
22t
c
May 2007 Márk Félegyházi (EPFL) 10
Stability: Nash equilibrium
p2
c1 c2
p1
c1 1.5,1.5 3,2
c2 2,3 1,1
Nash equilibrium: No player has an incentive to unilaterally deviate.* * *( , ) ( , ),i i i i i i iu s s u s s s S
Best response: Best strategy of player i given the strategies of others.
' '( ) : ( , ) ( , ),i i i i i i i i i ibr s s u s s u s s s S S
13t
c
22t
c
May 2007 Márk Félegyházi (EPFL) 11
Efficiency: Pareto-optimality
p2
c1 c2
p1
c1 1.5,1.5 3,2
c2 2,3 1,1
Price of anarchy: The ratio between the total payoff of players playing a socially-optimal (max. Pareto-optimal) strategy and a worst Nash equilibrium.
soi
iw NEi
i
uPOA
u
Pareto-optimality: The strategy profile spo is Pareto-optimal if:
' ': ( ) ( ),poi is u s u s i with strict inequality for at least one player i
13t
c
22t
c
Multi-Radio Channel Allocation in Wireless Networks
Non-Cooperative Users
May 2007 Márk Félegyházi (EPFL) 13
Related work► Channel allocation
– in cellular networks: fixed and dynamic: [Katzela and Naghshineh 1996, Rappaport 2002]
– in WLANs [Mishra et al. 2005]– in cognitive radio networks [Zheng and Cao 2005]
► Multi-radio networks– mesh networks [Adya et al. 2004, Alicherry et al. 2005]– cognitive radio [So et al. 2005]
► Competitive medium access– Aloha [MacKenzie and Wicker 2003, Yuen and Marbach 2005]– CSMA/CA [Konorski 2002, Čagalj et al. 2005]– WLAN channel coloring [Halldórsson et al. 2004]– channel allocation in cognitive radio networks [Cao and Zheng 2005, Nie
and Comaniciu 2005]
May 2007 Márk Félegyházi (EPFL) 14
Problem
► multi-radio devices► set of available channels
How to assign radios to available channels?
3d4d5d
6d
1d 2d
May 2007 Márk Félegyházi (EPFL) 15
System model (1/3)
3d4d5d
6d
1d 2d
2p
1p
3p
► – set of orthogonal channels (|| = C)
► – set of communicating pairs of devices (|| = N)
► sender controls the communication (sender and receiver are synchronized)
► single collision domain if they use the same channel
► devices have multiple radios► k radios at each device, k ≤ C
May 2007 Márk Félegyházi (EPFL) 16
System model (2/3)
► N communicating pairs of devices► C orthogonal channels► k radios at each device
,i xknumber of radios
by sender i on channel x
→
,i i xx C
k k
,x i xi N
k k
example:
3 2, 2p ck
Use multiple radios on one channel ?
, 1i xk Intuition:
23ck
34pk
May 2007 Márk Félegyházi (EPFL) 17
System model (3/3)► channels with the same properties► τ t(kx) – total throughput on any channel x
► τ(kx) – throughput per radio
May 2007 Márk Félegyházi (EPFL) 18
► selfish users (communicating pairs)► non-cooperative game GMRCA
– players → senders – strategy → channel allocation – payoff → total throughput
► strategy:
► strategy matrix:
► payoff:
Multi-radio channel allocation (MRCA) game
,1 ,,...,i i i Cs k k
1
N
s
S
s
, ( )i i i x xx C
u k k
May 2007 Márk Félegyházi (EPFL) 19
Lemma: If S* is a NE in GMRCA, then .
Use of all radios
Each player should use all of his radios.
p4 p4
,ik k i
Intuition: Player i is always better off deploying unused radios.
all channel allocations
Lem
ma
May 2007 Márk Félegyházi (EPFL) 20
Proposition: If S* is a NE in GMRCA, then dy,x ≤ 1, for any channel x and y.
Load-balancing channel allocation► Consider two arbitrary channels x and y in , where kx ≥ ky► distance: dx,y = kx – ky
all channel allocations
Lem
ma
Pro
posi
tion
May 2007 Márk Félegyházi (EPFL) 21
Nash equilibria (1/2)
Theorem 1: A channel allocation S* is a Nash equilibrium in GMRCA if for all i:
► dx,y ≤ 1 and
► ki,x ≤ 1.
p2
Nash Equilibrium: p4
Use one radio per channel.
all channel allocations
Lem
ma
Pro
posi
tion NE type 1
► Consider two arbitrary channels x and y in , where kx ≥ ky► distance: dx,y = kx – ky
May 2007 Márk Félegyházi (EPFL) 22
Nash equilibria (2/2)
Nash Equilibrium:
Theorem 2: A channel allocation S* is a Nash equilibrium in GMRCA if:
► dx,y ≤ 1,
► for any player i who has ki,x ≥ 2, x in ,
► for any player i who has ki,x ≥ 2 and x in +, ki,y ≥ ki,x – 1, for all y in –
Use multiple radios on certain channels.all channel allocations
Lem
ma
Pro
posi
tion NE type 1
NE type 2
,
( 1) ( 1)
( 1) ( )x x
i xx x
k kk
k k
► Consider two arbitrary channels x and y in , where kx ≥ ky► distance: dx,y = kx – ky
► loaded and less loaded channels: + and –
+–
May 2007 Márk Félegyházi (EPFL) 23
Efficiency (1/2)
1
1 1 1
t
t t tx x x x
POAN k
k k k kC
Corollary: If τt(kx) is constant (i.e., ideal TDMA), then any Nash equilibrium channel allocation is Pareto-optimal in GMRCA.
Theorem: In GMRCA , the price of anarchy is:
, 1x x
N k N kk k
C C
where
May 2007 Márk Félegyházi (EPFL) 24
Efficiency (2/2)
► In theory, if the total throughput function τt(kx) is constant POA = 1► In practice, there are collisions, but τt(kx) decreases slowly with kx (due to the
RTS/CTS method)
G. Bianchi, “Performance Analysis of the IEEE 802.11 Distributed Coordination Function,” in IEEE Journal on Selected Areas of Communication (JSAC), 18:3, Mar. 2000
May 2007 Márk Félegyházi (EPFL) 25
Convergence to NE (1/3)
p1 p1
N = 5, C = 6, k = 3
p2 p2
p4
p1
p3 p2 p5
p4
p5
p3
p3
p4
p5
c1 c2 c3c4 c5 c6
timep5: c2→c5
c6→c4p3: c2→c5
c6→c4c1→c3
p2: c2→c5p1: c2→c5
c6→c4
p1: c4→c6c5→c2
p4: idle
channelsp5
p3
p2
p1
p1
p4
Algorithm with imperfect info:► move links from “crowded”
channels to other randomly chosen channels
► desynchronize the changes► convergence is not ensured
May 2007 Márk Félegyházi (EPFL) 26
Convergence to NE (2/3)
3UB
Algorithm with imperfect info:► move links from “crowded”
channels to other randomly chosen channels
► desynchronize the changes► convergence is not ensured
xx
N kS k
C
C
Balance:
unbalanced (UB): best balance (NE):
Efficiency: ( ) ( )
( ) ( )UB
UB NE
S SS
S S
0 1S
15UB 7S
15 7 3
15 3 4S
May 2007 Márk Félegyházi (EPFL) 27
Convergence to NE (3/3)
N (# of pairs) 10
C (# of channels) 8
k (radios per device) 3
τ(1) (max. throughput) 54 Mbps
Summary and Future Work
May 2007 Márk Félegyházi (EPFL) 29
Summary – Multi-radio channel allocation
► wireless networks with multi-radio devices► users of the devices are selfish players► GMRCA – multi-radio channel allocation game► results for a Nash equilibrium:
– players should use all their radios– load-balancing channel allocation– two types of Nash equilibria– NE are efficient both in theory and practice
► fairness issues► coalition-proof equilibria► algorithms to achieve efficient NE:
– centralized algorithm with perfect information– distributed algorithm with imperfect information
May 2007 Márk Félegyházi (EPFL) 30
Summary of my research
► Ch 1: A tutorial on game theory► Ch. 2: Multi-radio channel allocation in wireless networks► Ch. 3: Packet forwarding in static ad-hoc networks► Ch. 4: Packet forwarding in dynamic ad-hoc networks► Ch. 5: Packet forwarding in multi-domain sensor networks► Ch. 6: Cellular operators in a shared spectrum► Ch. 7: Border games in cellular networks
Part II: Non-cooperative users
Part III: Non-cooperative network operators
Part I: Introduction to game theory
May 2007 Márk Félegyházi (EPFL) 31
Future research directions (1/3)
► Cognitive networks– Chapter 2: multi-radio channel allocation– adaptation is a fundamental property of cognitive devices– selfishness is threatening network performance
• primary (licensed) users• secondary (cognitive) users
– incentives are needed to prevent selfishness• frequency allocation• interference control
submitted: M. Félegyházi, M. Čagalj and J.-P. Hubaux, “Efficient MAC in Cognitive Radio Systems: A Game-Theoretic Approach,” submitted to IEEE JSAC, Special Issue on Cognitive Radios, 2008
May 2007 Márk Félegyházi (EPFL) 32
Future research directions (2/3)
► Coexistence of wireless networks– Chapter 6 and 7: wireless operators in shared spectrum– advancement of wireless technologies– alternative service providers
• small operators
• social community networks
– competition becomes more significant– coexistence results in nonzero-sum games
• mechanism to enforce cooperation
• competition improves services
in preparation: M. H. Manshaei, M. Félegyházi, J. Freudiger, J.-P. Hubaux, and P. Marbach, “Competition of Wireless Network Operators and Social Networks”
May 2007 Márk Félegyházi (EPFL) 33
Future research directions (3/3)
► Economics of security and privacy– cryptographic building blocks are quite reliable (some
people might disagree)– implementation fails due to economic reasons (3C)
• confusion in defining security goals • cost of implementation• complexity of usage
– privacy is often not among the security goals– incentives to implement correct security measures
• share liabilities• better synchronization• collaboration to prevent attacks
submitted: J. Freudiger, M. Raya, M. Félegyházi, and J.-P. Hubaux, “On Location Privacy in Vehicular Mix-Networks”
Extensions
May 2007 Márk Félegyházi (EPFL) 35
My research
Non-cooperative users► Multi-radio channel allocation in wireless networks► Packet forwarding in static ad-hoc networks► Packet forwarding in dynamic ad-hoc networksNon-cooperative network operators► Packet forwarding in multi-domain sensor networks► Cellular operators in a shared spectrum► Border games in cellular networks
May 2007 Márk Félegyházi (EPFL) 36
Thesis contributions (Ch. 1: A tutorial on game theory)
► facilitate the application of game theory in wireless networks
M. Félegyházi and J.-P. Hubaux, “Game Theory in Wireless Networks: A Tutorial,” submitted to ACM Communication Surveys, 2006
May 2007 Márk Félegyházi (EPFL) 37
Thesis contributions(Ch. 2: Multi-radio channel allocation in wireless
networks)► NE are efficient and sometimes fair, and they can be reached
even if imperfect information is available
3d4d5d
6d
1d 2d
2p
1p
3p
► load-balancing Nash equilibria– each player has one radio per
channel– some players have multiple radios
on certain channels► NE are Pareto-efficient both in
theory and practice► fairness issues► coalition-proof equilibria► convergence algorithms to
efficient NE
M. Félegyházi, M. Čagalj, S. S. Bidokhti, and J.-P. Hubaux, “Non-cooperative Multi-radio Channel Allocation in Wireless Networks,” in Proceedings of Infocom 2007, Anchorage, USA, May 6-12, 2007
May 2007 Márk Félegyházi (EPFL) 38
Thesis contributions(Ch. 3: Packet forwarding in static ad-hoc networks)
► incentives are needed to promote cooperation in ad hoc networks
► model and meta-model using game theory
► dependencies / dependency graph► study of NE
– in theory, NE based on cooperation exist
– in practice, the necessary conditions for cooperation do not hold
► part of the network can still cooperate
M. Félegyházi, L. Buttyán and J.-P. Hubaux, “Nash Equilibria of Packet Forwarding Strategies in Wireless Ad Hoc Networks,” in Transactions on Mobile Computing (TMC), vol. 5, nr. 5, May 2006
May 2007 Márk Félegyházi (EPFL) 39
Thesis contributions(Ch. 4: Packet forwarding in dynamic ad-hoc networks)
► mobility helps cooperation in ad hoc networks
► spontaneous cooperation exists on a ring (theoretical)
► cooperation resistant to drift (alternative cooperative strategies) to some extent
► in reality, generosity is needed► as mobility increases, less
generosity is needed
M. Félegyházi, L. Buttyán and J.-P. Hubaux, “Equilibrium Analysis of Packet Forwarding Strategies in Wireless Ad Hoc Networks - the Dynamic Case,” Technical report - LCA-REPORT-2003-010, 2003
May 2007 Márk Félegyházi (EPFL) 40
Thesis contributions(Ch. 5: Packet forwarding in multi-domain sensor
networks)► sharing sinks is beneficial and sharing sensors is also in
certain scenarios
► energy saving gives a natural incentive for cooperation
► sharing sinks► with common sinks, sharing
sensors is beneficial– in sparse networks– in hostile environments
M. Félegyházi, L. Buttyán and J.-P. Hubaux, “Cooperative Packet Forwarding in Multi-Domain Sensor Networks,” in PerSens 2005, Kauai, USA, March 8, 2005
May 2007 Márk Félegyházi (EPFL) 41
Thesis contributions(Ch. 6: Cellular operators in a shared spectrum)
► both cooperation (low powers) and defection (high powers) exist, but cooperation can be enforced by punishments
► wireless operators compete in a shared spectrum
► single stage game– various Nash equilibria in the grid
scenario, depending on cooperation parameters
► repeated game– RMIN (cooperation) is enforceable
with punishments► general scenario = arbitrary ranges
– the problem is NP-complete
M. Félegyházi and J.-P. Hubaux, “Wireless Operators in a Shared Spectrum,” in Proceedings of Infocom 2006, Barcelona, Spain, April 23-29, 2006
May 2007 Márk Félegyházi (EPFL) 42
Thesis contributions(Ch. 7: Border games in cellular networks)
► operators have an incentive to adjust their pilot power on the borders
► competitive power control on a national border
► power control game– operators have an incentive to be
strategic– NE are efficient, but they use high
power► simple convergence algorithm► extended game corresponds to the
Prisoner’s Dilemma
M. Félegyházi, M. Čagalj, D. Dufour, and J.-P. Hubaux, “Border Games in Cellular Networks,” in Proceedings of Infocom 2007, Anchorage, USA, May 6-12, 2007
May 2007 Márk Félegyházi (EPFL) 43
Selected publications (à la Prof. Gallager)
► M. Félegyházi, M. Čagalj, S. S. Bidokhti, and J.-P. Hubaux, “Non-Cooperative Multi-Radio Channel Allocation in Wireless Networks,” in Infocom 2007
► M. Félegyházi, M. Čagalj, D. Dufour, and J.-P. Hubaux, “Border Games in Cellular Networks,” in Infocom 2007
► M. Félegyházi, L. Buttyán and J.-P. Hubaux, “Nash Equilibria of Packet Forwarding Strategies in Wireless Ad Hoc Networks,” in IEEE Transactions on Mobile Computing (TMC), vol. 5, nr. 5, 2006
May 2007 Márk Félegyházi (EPFL) 44
Fairness
Nash equilibria (fair) Nash equilibria (unfair)
Theorem: A NE channel allocation S* is max-min fair iff
min min
, , , ,i x j xx x
k k i j
C C
N
Intuition: This implies equality: ui = uj, i,j
May 2007 Márk Félegyházi (EPFL) 45
Centralized algorithm
Assign links to the channels sequentially.
p1 p1 p1p1 p2p2
p2p2 p3 p3 p3p3
p4 p4 p4p4
May 2007 Márk Félegyházi (EPFL) 46
Thesis contributions
► Ch 1: A tutorial on game theory– facilitate the application of game theory in wireless networks
► Ch. 2: Multi-radio channel allocation in wireless networks– NE are efficient and sometimes fair, and the fair NE can be reached even
if imperfect information is available► Ch. 3: Packet forwarding in static ad-hoc networks
– incentives are needed to promote cooperation in ad hoc networks► Ch. 4: Packet forwarding in dynamic ad-hoc networks
– mobility helps cooperation in ad hoc networks► Ch. 5: Packet forwarding in multi-domain sensor networks
– sharing sinks is beneficial and sharing sensors is also in certain scenarios► Ch. 6: Cellular operators in a shared spectrum
– both cooperation (low powers) and defection (high powers) exist, but cooperation can be enforced by punishments
► Ch. 7: Border games in cellular networks – operators have an incentive to adjust their pilot power on the borders