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Approximate Continuous Query Answering over Streams and Dynamic Linked Data Sets


Soheila Dehghanzadeh, Daniele Dell’Aglio, Shen Gao, Emanuele Della Valle, Alessandra Mileo, Abraham Bernstein3

Publication Type: 
Edited Conference Meeting Proceeding
To perform complex tasks, RDF Stream Processing Web applications evaluate continuous queries over streams and quasi-static (background) data. While the former are pushed in the application, the latter are continuously retrieved from the sources. As soon as the back- ground data increase the volume and become distributed over the Web, the cost to retrieve them increases and applications become unresponsive. In this paper, we address the problem of optimizing the evaluation of these queries by leveraging local views on background data. Local views enhance performance, but require maintenance processes, because changes in the background data sources are not automatically reflected in the application. We propose a two-step query-driven maintenance process to maintain the local view: it exploits information from the query (e.g., the sliding window definition and the current window content) to maintain the local view based on user-defined Quality of Service constraints. Experimental evaluation show the effectiveness of the approach
Conference Name: 
Int'l Conferene on Web Engineering
Digital Object Identifer (DOI): 
10.1007/978-3-319-19890-3 20
Publication Date: 
Research Group: 
National University of Ireland, Galway (NUIG)
Open access repository: 
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