On enhancing scalability for distributed RDF/S stores

Tsatsanifos, George; Sacharidis, Dimitris; Sellis, Timos

doi:10.1145/1951365.1951384

Cited by 19 publications

(14 citation statements)

References 35 publications

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“…Future work will be devoted to compare the efficiency and effectiveness achieved by our framework with the ones of other approches well-known in literature, such as [7].…”

Section: Discussionmentioning

confidence: 99%

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SemTree: An index for supporting semantic retrieval of documents

Amato

Santo

Gargiulo

et al. 2015

2015 31st IEEE International Conference on Data Engineering Workshops

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Abstract-In this paper, we propose SemTree, a novel semantic index for supporting retrieval of information from huge amount of document collections, assuming that semantics of a document can be effectively expressed by a set of (subject, predicate, object) statements as in the RDF model. A distributed version of KD Tree has been then adopted for providing a scalable solution to the document indexing, leveraging the mapping of triples in a vectorial space. We investigate the feasibility of our approach in a real case study, considering the problem of finding inconsistencies in documents related to software requirements and report some preliminary experimental results.

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“…Future work will be devoted to compare the efficiency and effectiveness achieved by our framework with the ones of other approches well-known in literature, such as [7].…”

Section: Discussionmentioning

confidence: 99%

“…The problem of supporting in a scalable way the fast retrieval of triples related to various pattern queries by trans lating them into multi-dimensional range queries has been also faced in [7]. Differently from our approach, the authors adopt an RDF store that is built on the top of a distributed multi dimensional index structure.…”

Section: Introductionmentioning

confidence: 99%

SemTree: An index for supporting semantic retrieval of documents

Amato

Santo

Gargiulo

et al. 2015

2015 31st IEEE International Conference on Data Engineering Workshops

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“…Unlike the relational database community, the Semantic Web community uses a very different data model, which is RDF. Tsatsanifos et al [2011] present MIDAS-RDF, a distributed P2P RDF/S repository that is built on top of a distributed multi-dimensional index structure. It · Qin et al…”

Section: 23mentioning

confidence: 99%

When things matter: A survey on data-centric internet of things

Qin

Sheng

Falkner

et al. 2016

Journal of Network and Computer Applications

312

167

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With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machineto-human and machine-to-machine communication with the physical world. IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, but several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article reviews the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed.

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“…Distributed approaches represented by DARQ [3] and SemWIQ [4]. Indexed approaches represented by MIDAS-RDF [5] and QTree [6].…”

Section: Storage Approachmentioning

confidence: 99%

A Cloud-based Storage and Retrieval Solution for RDF Data

2019

Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering

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In recent years, RDF (Resource Description Framework) has been widely recognized as a standard data storage format. There is a real issue that how to store and retrieve RDF data efficiently, because it is the foundation of all semantic-based application development. In this paper, we propose a novel storage and retrieval solution based on cloud and R*-tree. Different to existing approaches, we use cloud-based storage approach to compress RDF data, meanwhile R*-tree is adapted to retrieve compressed data. The advantage is that it not only reduces the local storage pressure but also improves the retrieval performance compare to existing approaches. Because we separate the storage and retrieval and adapt dictionary-based compression approaches, in terms of security and flexibility, our solution is better than existing approaches.

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On enhancing scalability for distributed RDF/S stores

Cited by 19 publications

References 35 publications

SemTree: An index for supporting semantic retrieval of documents

SemTree: An index for supporting semantic retrieval of documents

When things matter: A survey on data-centric internet of things

A Cloud-based Storage and Retrieval Solution for RDF Data

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