A knowledge-oriented meta-framework for integrating sensor network infrastructures

Jabeur, Nafaâ; McCarthy, James D.; Xing, Xitao; Graniero, Phil A.

doi:10.1016/j.cageo.2008.04.006

Cited by 19 publications

(10 citation statements)

References 16 publications

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“…Although the OGC SWE effort has made enormous strides, a common sensor network architecture in the near future is not likely (Jabeur et al, 2009). Until that time an extensible and scalable interoperable cookie cutter method for creating sensor networks is essential.…”

Section: Resultsmentioning

confidence: 98%

An open geospatial consortium standards-based arctic climatology sensor network prototype

Rettig¹,

Beck²,

Rettig³

2011

Proceedings of the 2nd International Conference on Computing for Geospatial Research &Amp; Applications - COM.Geo '11

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We have constructed a prototype Open Geospatial Consortium (OGC) standards-based Arctic Climatology Sensor Network Prototype (ACSNP) in response to recent developments in sensor technology and Internet Protocol Suite (TCP/IP) wireless communications in Barrow, Alaska for the National Science Foundation (NSF). The OGC standards enable increased, interoperability, scalability, and extensibility for geospatial information at reduced cost. Our approach for the prototype is to integrate established technologies to create near-real-time geographic information networks (GINs). We linked a variety of meteorological and image sensors to a wide area wireless network in Barrow, Alaska. The network is a TCP/IP-based 700 Mhz WipLL network consisting of a 16 kilometer diameter local cloud as well as more distant fixed and mobile Iridium Open Port Units, that allow for global connectivity, at other remote research stations and on polar class ice breakers. Sensors linked to these wireless networks transfer their data to the Department of Energy (DOE) building in Barrow. The building houses two automatically populated mirrored File Transfer Protocol (FTP) servers running Microsoft Server 2003 within a virtualized environment. The data are automatically harvested from the remote site over redundant 4 X T-1 satellite links to the central data center in Cincinnati, Ohio where it is formatted to comply with the OGC database initiatives to create an OGC-compliant geodatabase within Microsoft SQL Server 2008. The final web publication is the result of a three part system; geodatabases, web services and web applications. We use ESRI's ArcGIS Server technology for retrieval and publication utilizing ESRI's compliance with OGC web services. These web services may then be embedded within OGC compliant clients, such as ESRI's ArcGIS Desktop and Google Earth for analysis and web applications. The Arctic Climatology Sensor Network Prototype is accessible at OpenSensorMap.com.

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Section: Resultsmentioning

confidence: 98%

An open geospatial consortium standards-based arctic climatology sensor network prototype

Rettig¹,

Beck²,

Rettig³

2011

Proceedings of the 2nd International Conference on Computing for Geospatial Research &Amp; Applications - COM.Geo '11

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“…Jabeur et al [16] presented a comprehensive sensor network cyberinfrastructure vision which they called knowledgeoriented meta-framework to facilitate the goal of getting the right Data from the right Area using the right Sensors at the right Time (DAST Principle). They also proposed a concept of a "Virtual Sensor Network" using an intelligent agents approach.…”

Section: "Semantic Sensor Network" "Semantic Sensor Web" and Ontolmentioning

confidence: 99%

A new framework for on-demand virtualization, repurposing and fusion of heterogeneous sensors

Liu

Hill

Rodríguez

et al. 2009

2009 International Symposium on Collaborative Technologies and Systems

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This paper describes our first step towards the realization of complex and large scale cross-organization virtual observatories by presenting a new semantically-enhanced "Sensor Network as a Service" (SNaaS) framework, which can repurpose existing sensor networks as needed and aggregate and fuse heterogeneous sensors into new virtual sensors in near-real-time. The architecture of this system allows users to create virtual sensors in a Web 2.0 collaborative map interface. Components of the system are highlighted in the paper including a semantically enhanced streaming data toolkit, virtual sensor ontologies and management middleware. Case studies are presented which can allow users to create new virtual rain gages based on the NEXRAD (Next Generation Weather Radar) data stream with or without in-situ rain gages on demand in a Chicago urban watershed testbed. The resulting virtual sensor data streams then can be published in multiple formats including a SWE-compliant one so that external SWE-compliant users and applications can seamlessly query and integrate them.

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“…Agent technology is one of the promising methods to achieve these goals. From the reported literature, agent approach has been applied for the network fault detection (Al-Kasassbeh and Adda, 2009), data fusion and management (Zhu et al, 2007), interoperable network framework (Jabeur et al, 2009), grid computing (Shi et al, 2006), mobile computing test system (Ilarri et al, 2009), and sensor network middleware to provide dynamic programming environments for flexible network management (Boulis et al, 2003;Szumel et al, 2005;Levis and Culler, 2002). An artificial immune system (AIS) is suitable to handle the great complexity of the reality (Castiglione et al, 2001).…”

Section: Introductionmentioning

confidence: 98%

Agent-based artificial immune system approach for adaptive damage detection in monitoring networks

Chen

2010

Journal of Network and Computer Applications

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A knowledge-oriented meta-framework for integrating sensor network infrastructures

Cited by 19 publications

References 16 publications

An open geospatial consortium standards-based arctic climatology sensor network prototype

An open geospatial consortium standards-based arctic climatology sensor network prototype

A new framework for on-demand virtualization, repurposing and fusion of heterogeneous sensors

Agent-based artificial immune system approach for adaptive damage detection in monitoring networks

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