SNEE: a query processor for wireless sensor networks

Galpin, L., Brenninkmeijer, C., Gray, A., Jabeen, F., Fernandes, A. and Paton, N.W. (2011) SNEE: a query processor for wireless sensor networks. Distributed and Parallel Databases, 29(1-2), pp. 31-85. (doi: 10.1007/s10619-010-7074-3)

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Publisher's URL: http://dx.doi.org/10.1007/s10619-010-7074-3

Abstract

A wireless sensor network (WSN) can be construed as an intelligent, large-scale device for observing and measuring properties of the physical world. In recent years, the database research community has championed the view that if we construe a WSN as a database (i.e., if a significant aspect of its intelligent behavior is that it can execute declaratively-expressed queries), then one can achieve a significant reduction in the cost of engineering the software that implements a data collection program for the WSN while still achieving, through query optimization, very favorable cost:benefit ratios. This paper describes a query processing framework for WSNs that meets many desiderata associated with the view of WSN as databases. The framework is presented in the form of compiler/optimizer, called SNEE, for a continuous declarative query language over sensed data streams, called SNEEql. SNEEql can be shown to meet the expressiveness requirements of a large class of applications. SNEE can be shown to generate effective and efficient query evaluation plans. More specifically, the paper describes the following contributions: (1) a user-level syntax and physical algebra for SNEEql, an expressive continuous query language over WSNs; (2) example concrete algorithms for physical algebraic operators defined in such a way that the task of deriving memory, time and energy analytical cost-estimation models (CEMs) for them becomes straightforward by reduction to a structural traversal of the pseudocode; (3) CEMs for the concrete algorithms alluded to; (4) an architecture for the optimization of SNEEql queries, called SNEE, building on well-established distributed query processing components where possible, but making enhancements or refinements where necessary to accommodate the WSN context; (5) algorithms that instantiate the components in the SNEE architecture, thereby supporting integrated query planning that includes routing, placement and timing; and (6) an empirical performance evaluation of the resulting framework.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Gray, Dr Alasdair
Authors: Galpin, L., Brenninkmeijer, C., Gray, A., Jabeen, F., Fernandes, A., and Paton, N.W.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Distributed and Parallel Databases
ISSN:0926-8782
Published Online:01 January 2011

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
402221Design, implementation and adaptation of sensor networks through multi-dimensional co-design (DIAS-MC)Joseph SventekEngineering & Physical Sciences Research Council (EPSRC)EP/C014774/1School of Computing Science