Distributed Selfish Replication

A commonly employed abstraction for studying the object placement problem for the purpose of Internet content distribution is that of a distributed replication group. In this work, the initial model of the distributed replication group of Leff et al. [CHECK END OF SENTENCE] is extended to the case t...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on parallel and distributed systems 2006-12, Vol.17 (12), p.1401-1413
Main Authors: Laoutaris, N., Telelis, O., Zissimopoulos, V., Stavrakakis, I.
Format: Article
Language:English
Subjects:
Access protocols
Algorithms
Bandwidth
Computational efficiency
Costs
Delay effects
Internet
IP networks
Mirrors
Network servers
Optimization
Peer to peer computing
Placement
Replication
Strategy
Studies
Utilities
Web and internet services
Web server
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A commonly employed abstraction for studying the object placement problem for the purpose of Internet content distribution is that of a distributed replication group. In this work, the initial model of the distributed replication group of Leff et al. [CHECK END OF SENTENCE] is extended to the case that individual nodes act selfishly, i.e., cater to the optimization of their individual local utilities. Our main contribution is the derivation of equilibrium object placement strategies that 1) can guarantee improved local utilities for all nodes concurrently as compared to the corresponding local utilities under greedy local object placement, 2) do not suffer from potential mistreatment problems, inherent to centralized strategies that aim at optimizing the social utility, and 3) do not require the existence of complete information at all nodes. We develop a baseline computationally efficient algorithm for obtaining the aforementioned equilibrium strategies and then extend it to improve its performance with respect to fairness. Both algorithms are realizable, in practice, through a distributed protocol that requires only a limited exchange of information.
ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2006.171