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14 - KanseiGenie: software infrastructure for resource management and programmability of wireless sensor network fabrics

from Part III - Protocols and practice

Published online by Cambridge University Press:  05 October 2012

Mukundan Sridharan
Affiliation:
The Ohio State University, USA
Wenjie Zeng
Affiliation:
The Ohio State University, USA
William Leal
Affiliation:
The Ohio State University, USA
Xi Ju
Affiliation:
The Ohio State University, USA
Rajiv Ramnath
Affiliation:
The Ohio State University, USA
Hongwei Zhang
Affiliation:
The Ohio State University, USA
Anish Arora
Affiliation:
The Ohio State University, USA
Byrav Ramamurthy
Affiliation:
University of Nebraska, Lincoln
George N. Rouskas
Affiliation:
North Carolina State University
Krishna Moorthy Sivalingam
Affiliation:
Indian Institute of Technology, Madras
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Summary

This chapter describes an architecture for slicing, virtualizing, and federating wireless sensor network (WSN) resources. The architecture, which we call KanseiGenie, allows users – be they sensing/networking researchers or application developers – to specify and acquire node and network resources as well as sensor data resources within one or more facilities for launching their programs. It also includes server-side measurement and management support for user programs, as well as client-side support for experiment composition and control. We illustrate KanseiGenie architectural concepts in terms of a current realization of KanseiGenie that serves WSN testbeds and application-centric fabrics at The Ohio State University and at Wayne State University.

Introduction

Deployed wireless sensor networks (WSN) have typically been both small-scale and focused on a particular application such as environmental monitoring or intrusion detection. However, recent advances in platform and protocol design now permit city-scale WSNs that can be deployed in such a way that new, unanticipated sensing applications can be accommodated by the network. This lets developers focus more on leveraging existing network resources and less on individual nodes.

Network abstractions for WSN development include APIs for scheduling tasks and monitoring system health as well as for in-the-field programming of applications, network components, and sensing components. As a result, WSN deployments have in several cases morphed from application-specific custom solutions to “WSN fabrics” that may be customized and reused in the field.

Type
Chapter
Information
Next-Generation Internet
Architectures and Protocols
, pp. 275 - 300
Publisher: Cambridge University Press
Print publication year: 2011

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References

,Global environment for network innovation. www.geni.net.
,Intelmote2: High-performance wireless sensor network node. http://docs.tinyos.net/index.php/Imote2.
,Kansei wireless sensor testbed. kansei.cse.ohio-state.edu.
,Layered sensing. www.wpafb.af.mil/shared/media/document/AFD-080820-005.pdf.
,Nested c: A language for embedded sensors. www.tinyos.net.
,NetEye wireless sensor testbed. http://neteye.cs.wayne.edu.
,Open resource control architecture. https://geni-orca.renci.org/trac/wiki/.
,Peoplenet mobility testbed. http://peoplenet.cse.ohio-state.edu.
,Stargate gateway devices. http://blog.xbow.com/xblog/stargate_xscale_platform/.
,Sunspots: A java based sensor mote. www.sunspotworld.com/.
,Telosb sensor motes. http://blog.xbow.com/xblog/telosb/.
,Xsm: Xscale sensor motes. www.xbow.com/Products/Product_pdf_files/Wireless_pdf/MSP410CA_Da%tasheet.pdf.
Arora, A., Gouda, M., Hallstrom, J. O., Herman, T., Leal, W. M., Sridhar, N. (2007). A state-based language for sensor-actuator networks. SIGBED Rev. 4, 3, 25–30.CrossRefGoogle Scholar
Kulathamani, V., Sridharan, M., Arora, A., Ramnath, R. (2008). Weave: Anarchitecture for tailoring urban sensing applications across multiple sensor fabrics. MODUS, International Workshop on Mobile Devices and Urban Sensing.

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