The Price of Selfishness in Network Coding

A game-theoretic framework is introduced for studying selfish user behavior in shared wireless networks. The investigation treats an n-unicast problem in a wireless network that employs a restricted form of network coding called reverse carpooling. Unicast sessions independently choose routes throug...

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Bibliographic Details
Published in:IEEE transactions on information theory 2012-04, Vol.58 (4), p.2349-2361
Main Authors: Marden, J. R., Effros, M.
Format: Article
Language:English
Subjects:
Applied sciences
Coding theory
Controllers
Cost function
Distributed control
Encoding
Exact sciences and technology
Game theory
Games
Information theory
Information, signal and communications theory
Nash equilibrium
Network coding
Organization and planning of networks (techniques and equipments)
price of anarchy (PoA)
Protocols
reverse carpooling
Switching and signalling
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Unicast
User behavior
Wireless networks
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Summary:A game-theoretic framework is introduced for studying selfish user behavior in shared wireless networks. The investigation treats an n-unicast problem in a wireless network that employs a restricted form of network coding called reverse carpooling. Unicast sessions independently choose routes through the network. The cost of a set of unicast routes is the number of wireless transmissions required to establish those connections using those routes. Game theory is employed as a tool for analyzing the impact of cost sharing mechanisms on the global system performance when each unicast independently and selfishly chooses its route to minimize its individual cost. The investigation focuses on the performance of stable solutions, where a stable solution is one in which no single unicast can improve its individual cost by changing its route. The results include bounds on the best- and worst-case stable solutions compared to the best performance that could be found and implemented using a centralized controller. The optimal cost sharing protocol is derived and the worst-case solution is bounded. That worst-case stable performance cannot be improved using cost-sharing protocols that are independent of the network structure.
ISSN:0018-9448
1557-9654
DOI:10.1109/TIT.2011.2177576