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					Game Authority for Robust and Scalable Distributed Selfish-Computer Systems
Shlomi Dolev, BGU (Israel) Elad M. Schiller, Chalmers (Sweden) Paul G. Spirakis, CTI (Greece) Philippas Tsigas, Chalmers (Sweden)

Distributed computing assumes Let’s play the prisoner identical programs. dilemma game. How to design distributed algorithms for the wild internet?

Use game theory for selfishcomputer systems.

The system designer

Game theory predicts: selfish-computer choose betray!
John Nash

A

B

Silent

Betray

OK... Let’s play Silent in a real system.
Betray

Yes, I trust game theory.

The system designer

O.K., we should explicitly enforce In a real system, the implicitwhere ofam the only rules I the game. authority…
they would be free to escape!

We need a distributed game authority.
The system designer

The Society Moral Code
• Complete anarchy exists without moral codes • Game authority founded over the moral majority
– choose and enforces the rules of the game – promote freedom of choice for the society’s benefit • We promote honestly selfish behavior for the sake of: • end-point creativity • motivation for success

The Society Moral Code
• Complete anarchy exists without moral codes • Game authority founded over the moral majority
– choose and enforces the rules of the game – promote freedom of choice for the society’s benefit Benefits • End-point success • that yields global success • Provable scalability • from the days of Greece • Provable robustness, still

Technical Contributions
Cost Reduction: • We replace the higher price of anarchy with the lower price of stability!

Technical Contributions
Cost Reduction: • We replace the higher price of anarchy with the lower price of stability!
Price of anarchy (PoA)
• Worst case ratio between: NE’s social cost, and the social optimum
Koutsoupias & Papadimitriou STACS’99 PoA Social optimum Worst NE

Good

Bad

Technical Contributions
Cost Reduction: • We replace the higher price of anarchy with the lower price of stability!
Price of stability (PoS)
• Best case ratio between: NE’s social cost, and the social optimum
Anshelevich et al.
FOCS'04

Social optimum PoS

Best NE

Worst NE

PoA Good Bad

Game Authority Implementation
• Can we assume that all components are selfish?
– impossible: Phy. layer game & Mac layer game &, … , & possible failures & imprecise utility • how to bound the PoA?

• Honest and moral based middleware tolerating
• Byzantine faults • transient faults • Facilitates interaction among honestly selfish agents

Application-layer: NE Social optimum Best PoS

Worst NE

∞

Honestly selfish agents (majority) Explicit PoA Middleware: Game Authority
Good Moral Code Bad

Implementation (cont.)
• How to decide on the preferable game? • How does the honest majority audit the game? • How to preserve privacy in simultaneous plays?
• Byzantine agreement • Cryptographic primitives • Game theory analysis

Your attention is appreciated
More details:
Technical report number TR-2006:9 Computer Science and Engineering Chalmers University of technology, 2006

Also, technical report, DELIS, 2006. Accessible via

http://delis.upb.de/docs/

Rabbi Akiva said: All is foreseen, but freedom of choice is given. The world is judged in goodness, yet all is proportioned to one's work. (Mishnah Pirkei Avot, Chapter 3, 19) ‫הכול צפוי, והרשות נתונה; ובטוב העולם נידון. והכול לפי‬ )‫רוב המעשה, אבל לא על פי המעשה . (פרקי אבות, ג` ט"ו‬


				
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