A scalable search engine for mass storage smart objects

Nicolas Anciaux 1, 2 Saliha Lallali 1, 2 Iulian Sandu Popa 1, 2 Philippe Pucheral 2, 1
2 SMIS - Secured and Mobile Information Systems
PRISM - Parallélisme, Réseaux, Systèmes, Modélisation, UVSQ - Université de Versailles Saint-Quentin-en-Yvelines, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR8144
Abstract : This paper presents a new embedded search engine designed for smart objects. Such devices are generally equipped with extremely low RAM and large Flash storage capacity. To tackle these conflicting hardware constraints, conventional search engines privilege either insertion or query scalability but cannot meet both requirements at the same time. Moreover, very few solutions support document deletions and updates in this context. In this paper, we introduce three design principles, namely Write-Once Partitioning, Linear Pipelining and Background Linear Merging, and show how they can be combined to produce an embedded search engine reconciling high insert/delete/update rate and query scalability. We have implemented our search engine on a development board having a hardware configuration representative for smart objects and have conducted extensive experiments using two representative datasets. The experimental results demonstrate the scalability of the approach and its superiority compared to state of the art methods.
Type de document :
Communication dans un congrès
31èmes journées Bases de Données Avancées (BDA), 2015, Île de Porquerolles, France. 2015
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Contributeur : Iulian Sandu Popa <>
Soumis le : mercredi 15 juillet 2015 - 14:32:09
Dernière modification le : mardi 23 octobre 2018 - 18:30:10


  • HAL Id : hal-01176462, version 1


Nicolas Anciaux, Saliha Lallali, Iulian Sandu Popa, Philippe Pucheral. A scalable search engine for mass storage smart objects. 31èmes journées Bases de Données Avancées (BDA), 2015, Île de Porquerolles, France. 2015. 〈hal-01176462〉



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