An Energy-Efficient Inter-organizational Wireless Sensor Data Collection Framework

Publication Year: 2015 Publication Type : ConferenceProceeding

Abstract:


Internet of Things (IoT) represents a cyberphysical world where physical things are interconnected on the Web. This paper presents an architecture designed for Energy-efficient Inter-organizational wireless sensor data collection Framework (EnIF). Environmental monitoring and urban sensing are two major application scenarios in IoT. Different from the traditional sensor environments, environmental sensing in IoT may require battery-powered nodes to perform the sensing tasks. Such a requirement raises a critical challenge to ensure that sensor data gathering can be collected in a timely and energy-efficient manner. Although numerous energy-efficient approaches for IoT scenarios have been proposed, previous works assumed the entire network was managed by a single organization in which the network establishment and communication have been pre-configured. This assumption is inconsistent with the fact that IoT is established in a federated network with heterogeneous devices controlled by different organizations. The aim of the framework is to enable a dynamic interorganizational collaborative topology towards saving energy from data transmissions using a service-oriented architecture.


BibTex:

@inproceedings{DBLP:conf/icws/ChangLDSSLL15,
    author = {Chii Chang and Seng W. Loke and Hai Dong and Flora D. Salim and Satish Narayana Srirama and Mohan Liyanage and Sea Ling},
    bibsource = {dblp computer science bibliography, https://dblp.org},
    biburl = {https://dblp.org/rec/conf/icws/ChangLDSSLL15.bib},
    booktitle = {2015 IEEE International Conference on Web Services, ICWS 2015, New York, NY, USA, June 27 - July 2, 2015},
    doi = {10.1109/ICWS.2015.90},
    editor = {John A. Miller and Hong Zhu},
    pages = {639--646},
    publisher = {IEEE Computer Society},
    timestamp = {Mon, 04 May 2020 13:17:48 +0200},
    title = {An Energy-Efficient Inter-organizational Wireless Sensor Data Collection Framework},
    url = {https://doi.org/10.1109/ICWS.2015.90},
    year = {2015}
}

Cite:

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