Title: Real-time query processing optimisation for wireless sensor networks

Authors: Ousmane Diallo; Joel J.P.C. Rodrigues; Mbaye Sene; Feng Xia

Addresses: Instituto de Telecomunicações, Department of Informatics, University of Beira Interior, Rua Marquês D’Ávila e Bolama, Covilhã 6201-001, Portugal; Department of Informatics, University of Assane Seck of Ziguinchor, Ziguinchor BP 523, Senegal ' Instituto de Telecomunicações, Department of Informatics, University of Beira Interior, Rua Marquês D’Ávila e Bolama, Covilhã 6201-001, Portugal; University ITMO, Saint Petersburg, Russia ' Department of Mathematics and Informatics, UCAD Avenue Cheikh Anta Diop, BP 5005, Dakar, Senegal ' School of Software, Dalian University of Technology, Development Zone, Dalian 116620, China

Abstract: Wireless sensor networks (WSNs) have been focused by many and high-relevant works. Nowadays, because of time-critical tasks of applications, one of the new challenges faced in WSNs is to handle real-time data storage and query. Since in such networks energy is the crucial resource, it is challenging to design a query processing mechanism that meets both time constraints and energy. This paper addresses this challenge and proposes a new architecture that combines statistical modelling techniques with the distributed approach and a query processing algorithm to optimise the real-time user query processing. Such statistical model provides good approximate answers of queries with a given probabilistic confidence. This combination allows performing a query processing algorithm based on admission control that uses the error tolerance and the probabilistic confidence interval as admission parameters. The experiments based on real world as well as synthetic data sets demonstrate that the proposed solution optimises the real-time query processing to save more energy while meeting time constraints.

Keywords: WSNs; wireless sensor networks; real-time DBM; database management; query estimation; query optimisation; distribution; query processing; statistical modelling; energy consumption; energy efficiency; admission control; error tolerance; probabilistic confidence interval.

DOI: 10.1504/IJSNET.2015.069863

International Journal of Sensor Networks, 2015 Vol.18 No.1/2, pp.49 - 61

Received: 20 Sep 2013
Accepted: 18 Jan 2014
Published online: 15 Jun 2015 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article