Tree vector indexes: efficient range queries for dynamic content on peer-to-peer networks

Marzolla, Moreno; Mordacchini, Matteo; Orlando, Salvatore

doi:10.1109/pdp.2006.68

Cited by 12 publications

(11 citation statements)

References 14 publications

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“…Bivectors have been originally exploited to implement routing indexes for unstructured networks [24]. A bitvector is defined by partitioning the space into k intervals, and a vector B is defined…”

Section: Bitvectorsmentioning

confidence: 99%

dragon: Multidimensional range queries on distributed aggregation trees

Carlini

Lulli

Ricci

2016

Future Generation Computer Systems

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h i g h l i g h t s• We have defined and implemented a support for multidimensional range query in distributed systems.• We exploited space filling curves to support the multi dimensionality.• The proposal is based on the definition of a distributed aggregation tree.• We investigated several aggregation techniques.• The paper includes an extensive experimental analysis of the system and a comparison with a state of art proposal. a b s t r a c tDistributed query processing is of paramount importance in next-generation distribution services, such as Internet of Things (IoT) and cyber-physical systems. Even if several multi-attribute range queries supports have been proposed for peer-to-peer systems, these solutions must be rethought to fully meet the requirements of new computational paradigms for IoT, like fog computing. This paper proposes dragon, an efficient support for distributed multi-dimensional range query processing targeting efficient query resolution on highly dynamic data. In dragon nodes at the edges of the network collect and publish multi-dimensional data. The nodes collectively manage an aggregation tree storing data digests which are then exploited, when resolving queries, to prune the sub-trees containing few or no relevant matches. Multi-attribute queries are managed by linearizing the attribute space through space filling curves. We extensively analysed different aggregation and query resolution strategies in a wide spectrum of experimental set-ups. We show that dragon manages efficiently fast changing data values. Further, we show that dragon resolves queries by contacting a lower number of nodes when compared to a similar approach in the state of the art.

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Section: Bitvectorsmentioning

confidence: 99%

dragon: Multidimensional range queries on distributed aggregation trees

Carlini

Lulli

Ricci

2016

Future Generation Computer Systems

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“…Here node 2 P forwards the query to 3 P , 3 P sends the query back to 1 P , repeat it again, it will cause an infinite loop. In order to avoid loop we need improve the route policy, which is to attach an additional info such as node ID list to record all traversal nodes linked the local node [7].…”

Section: Querying Algorithm For Computable Resourcementioning

confidence: 99%

Computational Nodes Location using Spatial Points Clustering in P2P Network System

Zeng¹

2016

IJFGCN

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“…Crespo et al [5] introduced the notion of routing indexes in P2P systems as structures that, given a query, return a list of inter-esting neighbours (sources) based on a data structure conforming to lists of counts for keyword occurrences in documents. Based on this work, other variants of routing indexes have been proposed, e.g., based on one-dimensional histograms [22], Bloom Filters [23], bit vectors [19], or the QTree. A common feature across these systems is to use a hash function to map string data to a numerical data space.…”

Section: Related Workmentioning

confidence: 99%

Data summaries for on-demand queries over linked data

Harth

Hose

Karnstedt

et al. 2010

Proceedings of the 19th International Conference on World Wide Web

156

155

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Typical approaches for querying structured Web Data collect (crawl) and pre-process (index) large amounts of data in a central data repository before allowing for query answering. However, this time-consuming pre-processing phase however leverages the benefits of Linked Data -where structured data is accessible live and up-to-date at distributed Web resources that may change constantly -only to a limited degree, as query results can never be current. An ideal query answering system for Linked Data should return current answers in a reasonable amount of time, even on corpora as large as the Web. Query processors evaluating queries directly on the live sources require knowledge of the contents of data sources. In this paper, we develop and evaluate an approximate index structure summarising graph-structured content of sources adhering to Linked Data principles, provide an algorithm for answering conjunctive queries over Linked Data on the Web exploiting the source summary, and evaluate the system using synthetically generated queries. The experimental results show that our lightweight index structure enables complete and up-to-date query results over Linked Data, while keeping the overhead for querying low and providing a satisfying source ranking at no additional cost.

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Tree vector indexes: efficient range queries for dynamic content on peer-to-peer networks

Abstract: Locating data on peer-to-peer networks is a complex is

Cited by 12 publications

References 14 publications

dragon: Multidimensional range queries on distributed aggregation trees

dragon: Multidimensional range queries on distributed aggregation trees

Computational Nodes Location using Spatial Points Clustering in P2P Network System

Data summaries for on-demand queries over linked data

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