This paper introduces a framework for the optimization of a peer-to-peer (p2p) based content replication system, aiming at actively exploiting the presence of a centralized component that represents a recent trend in content delivery architectures. To this purpose, we formalize a real-time mixed-integer nonlinear programming problem over a discrete time dynamic system, and propose a hybrid random/nonlinear programming scheme that allows to find good solutions while remaining computationally feasible. Two performance indexes, representing different objectives of the content replication process (e.g., speed vs. improved resistance against node failures), are discussed. Simulative tests are presented to prove the effectiveness of the proposed solution, with respect to typical strategies adopted by existing systems.

Optimization of a peer-to-peer system for efficient content replication

C Cervellera;L Caviglione
2009

Abstract

This paper introduces a framework for the optimization of a peer-to-peer (p2p) based content replication system, aiming at actively exploiting the presence of a centralized component that represents a recent trend in content delivery architectures. To this purpose, we formalize a real-time mixed-integer nonlinear programming problem over a discrete time dynamic system, and propose a hybrid random/nonlinear programming scheme that allows to find good solutions while remaining computationally feasible. Two performance indexes, representing different objectives of the content replication process (e.g., speed vs. improved resistance against node failures), are discussed. Simulative tests are presented to prove the effectiveness of the proposed solution, with respect to typical strategies adopted by existing systems.
2009
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
OR in telecommunications
Peer-to-peer systems
Mixed-integer nonlinear programming.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/29518
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