Paper Info
Title
LENS: resource specification for wireless sensor network experimentation infrastructures
Abstract
As a first step towards predictable, repeatable WSN experimentation, we propose the resource specification language LENS (a.k.a. Language for Embedded Networked Sensing) for WSN experimentation infrastructures. Using the Resource Description Framework (RDF) and the Web Ontology Language (OWL), LENS defines a semantic ontology for WSN resources; LENS enables explicit control and measurement of uncertainty factors, and it enables reasoning about the relationships between WSN resources. Focusing on basic concepts of WSNs, LENS supports resource specification in a wide range of WSN experimentation infrastructures, and it is extensible to support potentially unforeseen technologies. LENS is also compatible with specification languages for other network resources such as optical networks. As a part of the NSF GENI initiative, we have implemented LENS in the KanseiGenie control framework, and LENS has been actively used to support experimentation in the federated WSN infrastructure involving Kansei and NetEye. Enabling reasoning about uncertainty factors in experimentation, LENS is expected to serve as a basis for developing methodologies and tools for predictable, repeatable WSN experimentation.
Year
DOI
Venue
2011
10.1145/2030718.2030727
WiNTECH@MOBICOM
Keywords
Field
DocType
resource specification,resource specification language lens,kanseigenie control framework,wsn experimentation infrastructure,federated wsn infrastructure,repeatable wsn experimentation,uncertainty factor,specification language,wireless sensor network experimentation,wsn resource,enabling reasoning,resource description framework,wireless sensor network,web ontology language
Specification language,Ontology,Resource (disambiguation),Computer science,Kansei,Extensibility,Wireless sensor network,RDF,Distributed computing,Ontology language
Conference
Citations 
PageRank 
References 
5
0.58
14
Authors
8
Name
Order
Citations
PageRank
Xi Ju1664.28
Hongwei Zhang293567.71
Wenjie Zeng3203.99
Mukundan Sridharan441237.96
Jing Li561.63
Anish Arora62974270.71
Rajiv Ramnath729450.42
Yufeng Xin823027.74