A Survey of Structured P2P Systems for RDF Data Storage and Retrieval

Filali, Imen; Bongiovanni, Francesco; Huet, Fabrice; Baude, Françoise

doi:10.1007/978-3-642-23074-5_2

Cited by 28 publications

(20 citation statements)

References 53 publications

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“…Most systems [7,14,20] construct a data summary of neighboring nodes or clusters to make a query forwarding decisions. Some algorithms exchange these filters between nodes to maintain their network [11].…”

Section: Query Evaluation With Approximate Membershipmentioning

confidence: 99%

Opportunistic Linked Data Querying Through Approximate Membership Metadata

Sande

Verborgh

Herwegen

et al. 2015

The Semantic Web - ISWC 2015

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Abstract.Between dereferencing and the protocol lies a largely unexplored axis of possible interfaces to Linked Data, each with its own combination of trade-offs. One of these interfaces is Triple Pattern Fragments, which allows clients to execute queries against low-cost servers, at the cost of higher bandwidth. Increasing a client's efficiency means lowering the number of requests, which can among others be achieved through additional metadata in responses. We noted that typical query evaluations against Triple Pattern Fragments require a significant portion of membership subqueries, which check the presence of a specific triple, rather than a variable pattern. This paper studies the impact of providing approximate membership functions, i.e., Bloom filters and Golombcoded sets, as extra metadata. In addition to reducing requests, such functions allow to achieve full result recall earlier when temporarily allowing lower precision. Half of the tested queries from a WatDiv benchmark test set could be executed with up to a third fewer requests with only marginally higher server cost. Query times, however, did not improve, likely due to slower metadata generation and transfer. This indicates that approximate membership functions can partly improve the client-side query process with minimal impact on the server and its interface.

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Section: Query Evaluation With Approximate Membershipmentioning

confidence: 99%

Opportunistic Linked Data Querying Through Approximate Membership Metadata

Sande

Verborgh

Herwegen

et al. 2015

The Semantic Web - ISWC 2015

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“…Hence, the Hungarian algorithm can be applied to get the optimal chunk scheduling. Formally, the assignment problem (2) can be rewritten into the following assignment problem: be an optimal solution to the assignment problem (5), then k ij R is an optimal solution to the mcardinality assignment problem (2).…”

Section: Nodes' Reliabilitymentioning

confidence: 99%

On the optimal scheduling in pull-based real-time P2P streaming systems: Layered and non-layered streaming

Bradai

Ahmed

2012

2012 IEEE International Conference on Communications (ICC)

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Abstract-During the last decade, we witnessed a rapid growth in deployment of pull-based P2P streaming applications. In these applications, each node selects some other nodes as its neighbors and requests streaming data from them. This scheme allows eliminating data redundancy and recovering from data loss, but it pushes the complexity to the receiver node side. In this paper, we theoretically study the scheduling problem in Pull-based P2P video streaming and we model it as an assignment problem. Then, we propose AsSched, new scheduling algorithm for layered streaming, in order to optimize the throughput and the delivery ratio of the system. In second time, we derive an optimal algorithm (NAsSched) for non layered streaming. The results of simulations show that our algorithms significantly outperform classic scheduling strategies especially in stern bandwidth constraints.

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“…They placed a strong emphasis in preserving some level of peer independence, and adapting gracefully to peers and/or datasets joining, respectively, leaving the network, which in turn complicates the application's resilience to failures, and maintaining some level of service. A survey on P2P-based RDF data management can be found in [36].…”

Section: Introductionmentioning

confidence: 99%

RDF in the clouds: a survey

2014

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The Resource Description Framework (RDF) pioneered by the W3C is increasingly being adopted to model data in a variety of scenarios, in particular data to be published or exchanged on the Web. Managing large volumes of RDF data is challenging, due to the sheer size, the heterogeneity, and the further complexity brought by RDF reasoning. To tackle the size challenge, distributed storage architectures are required. Cloud computing is an emerging paradigm massively adopted in many applications for the scalability, faulttolerance, and elasticity feature it provides, enabling the easy deployment of distributed and parallel architectures. In this article, we survey RDF data management architectures and systems designed for a cloud environment, and more generally, those large-scale RDF data management systems that can be easily deployed therein. We first give the necessary background, then describe the existing systems and proposals in this area, and classify them according to dimensions related to their capabilities and implementation techniques. The survey ends with a discussion of open problems and perspectives.

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A Survey of Structured P2P Systems for RDF Data Storage and Retrieval

Cited by 28 publications

References 53 publications

Opportunistic Linked Data Querying Through Approximate Membership Metadata

Opportunistic Linked Data Querying Through Approximate Membership Metadata

On the optimal scheduling in pull-based real-time P2P streaming systems: Layered and non-layered streaming

RDF in the clouds: a survey

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