Memorias de investigación
Artículos en revistas:
Scalable and topology-aware reconciliation on P2P networks
Año:2008

Áreas de investigación
  • Lenguaje de programación

Datos
Descripción
Collaborative applications are characterized by high levels of data sharing. Optimistic replication has been suggested as a mechanism to enable highly concurrent access to the shared data, whilst providing full application-defined consistency guarantees. Nowadays, there are a growing number of emerging cooperative applications adequate for Peer-to-Peer (P2P) networks. However, to enable the deployment of such applications in P2P networks, it is required a mechanism to deal with their high data sharing in dynamic, scalable and available way. Previous work on optimistic replication has mainly concentrated on centralized systems. Centralized approaches are inappropriate for a P2P setting due to their limited availability and vulnerability to failures and partitions from the network. In this paper, we focus on the design of a reconciliation algorithm designed to be deployed in large scale cooperative applications, such as P2P Wiki. The main contribution of this paper is a distributed reconciliation algorithm designed for P2P networks (P2P-reconciler). Other important contributions are: a basic cost model for computing communication costs in a DHT overlay network; a strategy for computing the cost of each reconciliation step taking into account the cost model; and an algorithm that dynamically selects the best nodes for each reconciliation step. Furthermore, since P2P networks are built independently of the underlying topology, which may cause high latencies and large overheads degrading performance, we also propose a topology-aware variant of our P2P-reconciler algorithm and show the important gains on using it. Our P2P-reconciler solution enables high levels of concurrency thanks to semantic reconciliation and yields high availability, excellent scalability, with acceptable performance and limited overhead.
Internacional
Si
JCR del ISI
Si
Título de la revista
DISTRIBUTED AND PARALLEL DATABASES
ISSN
0926-8782
Factor de impacto JCR
0,771
Información de impacto
Volumen
24
DOI
http://dx.doi.org/10.1007/s10619-008-7029-0
Número de revista
3
Desde la página
1
Hasta la página
43
Mes
DICIEMBRE
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Participantes
  • autora: Esther Pacitti INRIA and LINA, University of Nantes
  • autor: Manal El Dick INRIA and LINA, University of Nantes
  • Autor: Ricardo Jimenez Peris UPM
  • autor: Vidal Martins Pontifical Catholic University of Paraná

Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Distributed Systems Labs (LSD) Laboratorio de sistemas distribuidos
  • Departamento: Lenguajes y Sistemas Informáticos e Ingeniería de Software