An Adaptive Probabilistic Replication Method for Unstructured P2P Networks

Tsoumakos, Dimitrios; Roussopoulos, Nick

doi:10.1007/11914853_29

Cited by 8 publications

(6 citation statements)

References 16 publications

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“…On the contrary, when the queries are evenly distributed among data items, the proportional replication does not gain much in latency. The probabilistic replication lies between the above two [92,93]. Square-root replication is an example of the probabilistic replication.…”

Section: Data Availabilitymentioning

confidence: 98%

A conceptual model for data management and distribution in peer-to-peer systems

Aygün

Akkaya

et al. 2009

Peer-to-Peer Netw. Appl.

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While Peer-to-Peer (P2P) model gains significant attention in distributed computing, it is also expected to be a powerful model for information sharing. P2P systems are expected to provide exhaustive reliable computational resources and scalable accessibility. The data management and distribution in such systems requires storage, replication, data modeling, indexing, querying, retrieval, streaming, and topology management. While a lot of data management strategies have been proposed through the last years, these strategies have not been investigated with respect to a common model for P2P systems. However, since the services provided by the P2P systems are so diverse, it is very challenging to come up with a common layer-based model for all P2P systems. In this paper, we firstly propose a conceptual model for P2P systems, and then provide a classification and summary of data management and distribution strategies by referring to this model. The horizontal layers of the model correspond to modules of a P2P system whereas the columns are related to the services provided. The modules include base P2P service, storage, indexing, logical, service, and application modules. The services include security, querying, publish, join/leave, collaboration, and streaming. The paper concludes by providing a comprehensive list of data management and distribution strategies used in the existing P2P systems.

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Section: Data Availabilitymentioning

confidence: 98%

A conceptual model for data management and distribution in peer-to-peer systems

Aygün

Akkaya

et al. 2009

Peer-to-Peer Netw. Appl.

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“…To adapt to the dynamic behavior of the environment and the application access patterns, various solutions have been proposed in the literature [16,11,12,19]. Among these, the Adaptive Data Replication algorithm (ADR) described in [19] is particularly interesting, as it was shown to be convergent-optimal with respect to communication costs.…”

Section: Adaptive Data Replicationmentioning

confidence: 99%

“…Similarly to our paper, some works [17,18] integrate a communication model for their adaptive datareplication solutions. Other works have also adapted to the read-write pattern, e.g., in [7,16]. In addition to the read-write pattern, several objectives were defined to dictate the replication strategy.…”

Section: Related Workmentioning

confidence: 99%

Reliable Communication Infrastructure for Adaptive Data Replication

Allani

Garbinato

Malekpour

et al. 2009

On the Move to Meaningful Internet Systems: OTM 2009

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In this paper, we propose a data replication algorithm adaptive to unreliable environments. The data replication algorithm, named Adaptive Data Replication (ADR), has already an adaptiveness mechanism encapsulated in its dynamic replica placement strategy. Our extension of ADR to unreliable environments provides a data replication solution that is adaptive both in terms of replica placement and in terms of request routing. At the routing level, this solution takes the unreliability of the environment into account, in order to maximize reliable delivery of requests. At the replica placement level, the dynamically changing origin and frequency of read/write requests are analyzed, in order to define a set of replica that minimizes communication cost. Performance evaluation shows that this original combination of two adaptive strategies makes it possible to ensure high request delivery, while minimizing communication overhead in the system.

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“…Additionally, analysis of resource replication in the event of selfish server nodes is given in [21]. APRE [22] uses probabilistic search to achieve dynamic replication in unstructured networks.…”

Section: B Replicationmentioning

confidence: 99%

Replica Placement and Location using Distributed Hash Tables

Mahanti

Williamson

Arlitt

et al. 2007

32nd IEEE Conference on Local Computer Networks (LCN 2007)

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Abstract-Interest in distributed storage is fueled by demand for reliability and resilience combined with decreasing hardware costs. Peer-to-peer storage networks based on distributed hash tables are attractive for their efficient use of resources and resulting performance. The placement and subsequent efficient location of replicas in such systems remain open problems, especially (1) the requirement to update replicated content, (2) working in the absence of global information, and (3) determination of the locations in a dynamic system without introducing single points of failure.We present and evaluate a novel and versatile technique, replica enumeration, which allows for controlled replication and replica access. The possibility of enumerating and addressing individual replicas allows dynamic updates as well as superior performance without burdening the network with state information, yet taking advantage of locality information when available. We simulate, analyze, and prove properties of the system, and discuss some applications.

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An Adaptive Probabilistic Replication Method for Unstructured P2P Networks

Cited by 8 publications

References 16 publications

A conceptual model for data management and distribution in peer-to-peer systems

A conceptual model for data management and distribution in peer-to-peer systems

Reliable Communication Infrastructure for Adaptive Data Replication

Replica Placement and Location using Distributed Hash Tables

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