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  5. Combining sensor selection with routing and scheduling in wireless sensor networks
 
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Combining sensor selection with routing and scheduling in wireless sensor networks

Author(s)
Muldoon, Conor  
Trigoni, Niki  
O'Hare, G. M. P. (Greg M. P.)  
Uri
http://hdl.handle.net/10197/3510
Date Issued
2011-08-29
Date Available
2012-02-16T11:54:42Z
Abstract
In wireless sensor networks, determining the set of locations to activate sensors, such that the amount of information received is maximised, is an important task. With the model driven approach to sensor networks, a considerable amount of research has been conducted into the sensor selection problem, whereby informative locations to activate sensors are determined through the use of Gaussian Processes. Current approaches to sensor selection, however, do not take bandwidth constraints into consideration. When bandwidth is limited, the amount of time required to realise a given set of communication requests, in terms of rout- ing and scheduling, must be accounted for. Traditionally, in wireless sensor networks, sensor selection, routing, and scheduling are considered separately. These three processes, however, are highly coupled and the overall utility of the data collection process, in terms of the amount of information it produces, can be improved by integrating them. In this paper, we present two approaches to combining routing, scheduling, and sensor selection such that they inform each other so as to improve the performance of the network in the bandwidth limited case.
Sponsorship
Science Foundation Ireland
Irish Research Council for Science, Engineering and Technology
European Research Council
Type of Material
Conference Publication
Copyright (Published Version)
2011 ACM
Subjects

Sensor selection

Gaussian processes

Subject – LCSH
Wireless sensor networks
Gaussian processes
Language
English
Status of Item
Peer reviewed
Conference Details
Paper presented at the 8th International Workshop on Data Management for Sensor Networks (DMSN’11)‚ held in conjunction with the International Conference on Very Large Data Bases (VLDB)‚ Seattle, USA, 29 August 2011
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-sa/1.0/
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paper01.pdf

Size

666.48 KB

Format

Adobe PDF

Checksum (MD5)

7ae9072646acc4d84d87069db1b96312

Owning collection
Computer Science Research Collection
Mapped collections
CLARITY Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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