Research Article
From Kansei to KanseiGenie: Architecture of Federated, Programmable Wireless Sensor Fabrics
@INPROCEEDINGS{10.1007/978-3-642-17851-1_12, author={Mukundan Sridharan and Wenjie Zeng and William Leal and Xi Ju and Rajiv Ramnath and Hongwei Zhang and Anish Arora}, title={From Kansei to KanseiGenie: Architecture of Federated, Programmable Wireless Sensor Fabrics}, proceedings={Testbeds and Research Infrastructures. Development of Networks and Communities. 6th International ICST Conference, TridentCom 2010, Berlin, Germany, May 18-20, 2010, Revised Selected Papers}, proceedings_a={TRIDENTCOM}, year={2012}, month={10}, keywords={wireless sensor network federation fabrics resource specification ontology experiment specification GENI KanseiGenie}, doi={10.1007/978-3-642-17851-1_12} }- Mukundan Sridharan
Wenjie Zeng
William Leal
Xi Ju
Rajiv Ramnath
Hongwei Zhang
Anish Arora
Year: 2012
From Kansei to KanseiGenie: Architecture of Federated, Programmable Wireless Sensor Fabrics
TRIDENTCOM
Springer
DOI: 10.1007/978-3-642-17851-1_12
Abstract
This paper deals with challenges in federating wireless sensing fabrics. Federations of this sort are currently being developed in next generation global end-to-end experimentation infrastructures, such as GENI, to support rapid prototyping and hi-fidelity validation of protocols and applications. On one hand, federation should support access to diverse (and potentially provider-specific) wireless sensor resources and, on the other, it should enable users to uniformly task these resources. Instead of more simply basing federation upon a standard description of resources, we propose an architecture where the ontology of resource description can vary across providers, and a mapping of user needs to resources is performed to achieve uniform tasking. We illustrate one realization of this architecture, in terms of our refactoring the Kansei testbed to become the KanseiGenie federated fabric manager, which has full support for programmability, sliceability and federated experimentation over heterogeneous sensing fabrics.
