Chryssis Georgiou

Dr. Chryssis Georgiou

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Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 July 2013
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CAChrysovalandis Agathangelou
Chrysovalandis Agathangelou
CGChryssis Georgiou
Chryssis Georgiou
MMMarios Mavronicolas
Marios Mavronicolas

1 January 2009 in Journal of Parallel and Distributed Computing
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Journal Article
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CGChryssis Georgiou
Chryssis Georgiou
NNNicolas Nicolaou
Nicolas Nicolaou
ASAlexander A. Shvartsman
Alexander A. Shvartsman

30 November 2005 in Theoretical Computer Science
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Journal Article
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CGChryssis Georgiou
Chryssis Georgiou
DKDariusz R. Kowalski
Dariusz R. Kowalski
ASAlexander A. Shvartsman
Alexander A. Shvartsman

18 August 2008
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Conference Paper
Open access
CGChryssis Georgiou
Chryssis Georgiou
SGSeth Gilbert
Seth Gilbert
RGRachid Guerraoui
Rachid Guerraoui
DKDariusz R. Kowalski
Dariusz R. Kowalski

1 August 2013 in Concurrency and Computation: Practice and Experience
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ECEvgenia Christoforou
Evgenia Christoforou
AAAntonio Fernández Anta
Antonio Fernández Anta
CGChryssis Georgiou
Chryssis Georgiou
MMMiguel A. Mosteiro
Miguel A. Mosteiro
ASAngel Sánchez
Angel Sánchez
We consider Internet-based master–worker task computations, such as SETI@home, where a master process sends tasks, across the Internet, to worker processes; workers execute and report back some result. However, these workers are not trustworthy, and it might be at their best interest to report incorrect results. In such master–worker computations, the behavior and the best interest of the workers might change over time. We model such computations using evolutionary dynamics, and we study the conditions under which the master can reliably obtain task results. In particular, we develop and analyze an algorithmic mechanism based on reinforcement learning to provide workers with the necessary incentives to eventually become truthful. Our analysis identifies the conditions under which truthful behavior can be ensured and bounds the expected convergence time to that behavior. The analysis is complemented with illustrative simulations. Copyright © 2013 John Wiley & Sons, Ltd.

1 April 2013 in Journal of the ACM
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Journal Article
Open access
CGChryssis Georgiou
Chryssis Georgiou
SGSeth Gilbert
Seth Gilbert
RGRachid Guerraoui
Rachid Guerraoui
DKDariusz R. Kowalski
Dariusz R. Kowalski
We study the complexity of gossip in an asynchronous, message-passing fault-prone distributed system. We show that an adaptive adversary can significantly hamper the spreading of a rumor, while an oblivious adversary cannot. The algorithmic techniques proposed in this article can be used for improving the message complexity of distributed algorithms that rely on an all-to-all message exchange paradigm and are designed for an asynchronous environment. As an example, we show how to improve the message complexity of asynchronous randomized consensus.