Sensor Systems and Software. 4th International ICST Conference, S-Cube 2013, Lucca, Italy, June 11-12, 2013, Revised Selected Papers

Research Article

IRIS: A Flexible and Extensible Experiment Management and Data Analysis Tool for Wireless Sensor Networks

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  • @INPROCEEDINGS{10.1007/978-3-319-04166-7_7,
        author={Richard Figura and Chia-Yen Shih and Songwei Fu and Roberta Daidone and Sascha Jungen and Pedro Marr\^{o}n},
        title={IRIS: A Flexible and Extensible Experiment Management and Data Analysis Tool for Wireless Sensor Networks},
        proceedings={Sensor Systems and Software. 4th International ICST Conference, S-Cube 2013, Lucca, Italy, June 11-12, 2013, Revised Selected Papers},
        proceedings_a={S-CUBE},
        year={2014},
        month={6},
        keywords={Wireless sensor networks Data processing Experiment management Data analysis Data visualization},
        doi={10.1007/978-3-319-04166-7_7}
    }
    
  • Richard Figura
    Chia-Yen Shih
    Songwei Fu
    Roberta Daidone
    Sascha Jungen
    Pedro Marrón
    Year: 2014
    IRIS: A Flexible and Extensible Experiment Management and Data Analysis Tool for Wireless Sensor Networks
    S-CUBE
    Springer
    DOI: 10.1007/978-3-319-04166-7_7
Richard Figura1,*, Chia-Yen Shih1,*, Songwei Fu1,*, Roberta Daidone2,*, Sascha Jungen1,*, Pedro Marrón1,*
  • 1: University of Duisburg-Essen
  • 2: University of Pisa
*Contact email: richard.figura@uni-due.de, chia-yen.shih@uni-due.de, songwei.fu@uni-due.de, r.daidone@iet.unipi.it, sascha.jungen@stud.uni-due.de, pjmarron@uni-due.de

Abstract

Performing field experiments is a key step to validate the design of a Wireless Sensor Network (WSN) application and to evaluate its performance under various conditions. We present an experiment management and data analysis tool called that offers effective management of various configuration settings forWSN experiments. One special feature of IRIS is its extensibility. That is, IRIS allows the developer to define customized functions for application-specific data analysis and performance evaluation. Other main features include: enabling the interaction with the deployedWSN at runtime for fine tuning the experiments and providing graphical presentation for visualizing the collected data as well as the processed results. We highlight the advantages of IRIS for the WSN application development in different experiment phases. Furthermore, we demonstrate the usefulness of IRIS with two real-life WSN applications to show that IRIS can be integrated to develop an application and can greatly help in performing experiments more efficiently.