ScienceDirect® Home Skip Main Navigation Links
You have guest access to ScienceDirect. Find out more.
 
Home
Browse
My Settings
Alerts
Help
 Quick Search
 Search tips (Opens new window)
    Clear all fields    
advertisementadvertisement
Computer Networks
Volume 52, Issue 9, 26 June 2008, Pages 1721-1731
 
Font Size: Decrease Font Size  Increase Font Size
 Abstract - selected
Article
Purchase PDF (367 K)

  E-mail Article   
  Add to my Quick Links   
Bookmark and share in 2collab (opens in new window)
Request permission to reuse this article
  Cited By in Scopus (0)
 
 
 
Related Articles in ScienceDirect
View More Related Articles
 
View Record in Scopus
 
doi:10.1016/j.comnet.2008.02.009    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2008 Elsevier B.V. All rights reserved.

Selfishness, collusion and power of local search for the ADMs minimization problemstar, open

Michele Flamminia, E-mail The Corresponding Author, Gianpiero Monacoa, Corresponding Author Contact Information, E-mail The Corresponding Author, Luca Moscardellia, E-mail The Corresponding Author, Mordechai Shalomb, E-mail The Corresponding Author and Shmuel Zaksc, E-mail The Corresponding Author

aUniversità degli Studi dell’Aquila, Department of Computer Science, Via Vetoio Coppito, 67100 L’Aquila, Italy bTelHai Academic College, Upper Galilee 12210, Israel cDepartment of Computer Science, Technion, Haifa, Israel

Received 28 September 2007; 
accepted 23 February 2008. 
Responsible Editor: J. Sole-Pareta. 
Available online 18 March 2008.

Purchase the full-text article



References and further reading may be available for this article. To view references and further reading you must purchase this article.

Abstract

We consider non-cooperative games in all-optical networks where users share the cost of the used ADM switches for realizing given communication patterns. We show that the two fundamental cost sharing methods, Shapley and Egalitarian, induce polynomial converging games with price of anarchy at most View the MathML source, regardless of the network topology. Such a bound is tight even for rings. Then, we show that if collusion of at most k players is allowed, the Egalitarian method yields polynomially converging games with price of collusion between View the MathML source and View the MathML source. This result is very interesting and quite surprising, as the best known approximation ratio, that is View the MathML source, can be achieved in polynomial time by uncoordinated evolutions of collusion games with coalitions of increasing size. Finally, the Shapley method does not induce well defined collusion games, but can be exploited in the definition of local search algorithms with local optima arbitrarily close to optimal solutions. This would potentially generate PTAS, but unfortunately the arising algorithm might not converge. The determination of new cost sharing methods or local search algorithms reaching a compromise between Shapley and Egalitarian is thus outlined as being a promising and worth pursuing investigating direction.

Keywords: Optical networks; Add-drop multiplexer (ADM); Nash equilibria; Price of anarchy; Price of collusion

Article Outline

1. Introduction
1.1. Background
1.2. Our contribution
2. Model and preliminary results
3. Price of anarchy
4. Price of collusion
5. Local search and concluding remarks
References
Vitae




Computer Networks
Volume 52, Issue 9, 26 June 2008, Pages 1721-1731
 
Home
Browse
My Settings
Alerts
Help
Elsevier.com (Opens new window)
About ScienceDirect  |  Contact Us  |  Information for Advertisers  |  Terms & Conditions  |  Privacy Policy
Copyright © 2008 Elsevier B.V. All rights reserved. ScienceDirect® is a registered trademark of Elsevier B.V.