Acyclic Preference Systems in P2P Networks

Abstract

The original publication is available at www.springerlink.comInternational audienceIn this work we study preference systems suitable for the Peer-to-Peer paradigm. Most of them fall in one of the three following categories: global, symmetric and complementary. All these systems share an acyclicity property. As a consequence, they admit a stable (or Pareto efficient) configuration, where no participant can collaborate with better partners than their current ones. We analyze the representation of such preference systems and show that any acyclic system can be represented with a symmetric mark matrix. This gives a method to merge acyclic preference systems while retaining the acyclicity property. We also consider properties of the corresponding collaboration graph, such as clustering coefficient and diameter. In particular, the study of the example of preferences based on real latency measurements shows that its stable configuration is a small-world graph

Self-stabilization in preference-based systems

“…b -matching theory and its variants have already applications in a variety of real-world situations, including dating agencies, college admissions, roommates attributions, assignment of graduating medical students to their first hospital appointment, or kidney exchanges programs [11,14,15,24,25]. Regarding decentralized networks, b -matching already gave a theoretical proof for upload/download correlations in incentive networks like BitTorrent [10] and highlighted small-world phenomena in latencybased networks [8].…”

“… Gai et al showed that symmetric marks can define all possible acyclic preferences, including global preferences[8]. Therefore it is natural to consider how close to global preferences a symmetric matrix is.…”

Stable Marriage and Roommates Problems with Restricted Edges: Complexity and Approximability

“…Stability as an underlying concept is also used to allocate graduating medical students to hospitals in many countries [8]. sr on the other hand has applications in the area of P2P networks [9].…”

A new Airport Collaborative Decision Making algorithm based on Deferred Acceptance in a two-sided market

“…Dealing with this market by using the DA-CDM model enables 133 assigning flights to slots through a one-to-one relationship that 134 respects the preferences of each allocation and is always guaran-135 teed to provide a stable result (Vossen & Ball, 2006 (Ergin & Sonmez, 2006;Gai et al, 2007;Roth et al, 2004). 244 As the use of runways of an airport can be considered as a 245 limited resource of aeronautical and airport infrastructure, the 246 matching markets models can be associated to ATFM processes 247 considering the demand and capacity of runways for aircraft.…”

“…76 This model, based on Matching Markets Mechanisms of the Game 77 Theory, allows to include the preferences of the Airport 78 Management, next to those of the ATC agents and the airlines. 79 The choice of Game Theory for our solution is due to the fact 80 that such approaches enable the incorporation of the preferences 81 of different stakeholders (Sonmez & Unver, 2011) and have been 82 successfully implemented in labor markets (Roth & Sotomayor,83 1989), school admission process (Ergin & Sonmez, 2006), P2P 84 networks (Gai et al, 2007), and organ donation markets (Roth, 85 Sonmez, & Unver, 2004), and generally in domains that involve (Balakrishnan, 2007;Pinheiro, Vinicius, Weigang, Melo, & Alba, 88 2007; Weigang, Alves, & Omar, 1997. Intelligent systems 89 for the reallocation of flights, gate scheduling, and related prob-90 lems (Chan, Chow, So, & Chan, 2012;Cheng, Ho, & Kwan, 2012;91 Genc, Erol, Eksin, Berber, & Guleryuz, 2012;Jo, Jung, & Yang, 92 1997; Kuwata & Oohama, 1997) anteed that airlines report their cancellations due to the lack of 124 incentive to do so (Schummer & Rakesh, 2013).…”