Title :
Self-Stabilization in Preference-Based Networks
Author_Institution :
Orange Labs, Orange
Abstract :
Participants in a decentralized system often use some local ranking information in selecting effective collaborations. We say that such systems are preference-based for most practical types of preferences, such systems converge towards a unique stable configuration. In this paper, we investigate the speed and quality of the convergence process with respect to the model parameters. Our results provide insight into the design of system parameters, such as the number of connections or the algorithm for choosing new partners.
Keywords :
multivariable systems; peer-to-peer computing; stability; convergence process; decentralized system; local ranking information; model parameters; preference-based networks; self-stabilization; stable configuration; system parameters; Algorithm design and analysis; Bandwidth; Convergence; Educational institutions; Greedy algorithms; Hospitals; International collaboration; Peer to peer computing; Protocols; Symmetric matrices;
Conference_Titel :
Peer-to-Peer Computing, 2007. P2P 2007. Seventh IEEE International Conference on
Conference_Location :
Galway
Print_ISBN :
978-0-7695-2986-8
DOI :
10.1109/P2P.2007.16
