research-article

Semantic web based architecture for managing hardware heterogeneity in wireless sensor network

Authors:

Siniša Nikolić,

Valentin Penca,

Milan Segedinac,

Zora KonjovićAuthors Info & Claims

WIMS '11: Proceedings of the International Conference on Web Intelligence, Mining and Semantics

Article No.: 42, Pages 1 - 9

https://doi.org/10.1145/1988688.1988738

Published: 25 May 2011 Publication History

Abstract

Wireless Sensor Networks (WSNs) are vivid and relatively new paradigm. Usually they are built for the specific purposes which, in the case of large systems of WSNs, can result in high hardware heterogeneity. In this paper we have proposed an ontology-based model aimed at resolving the hardware heterogeneity in large systems of WSNs, and the GLOSENT architecture that facilitates integration of heterogeneous WSNs. In addition, as a case study the concrete SN device SunSPOT is represented using proposed ontology.

References

[1]

Avancha, S., Patel, C., Joshi, A. 2004. Ontology-driven adaptive sensor networks. Mobile and Ubiquitous Systems: Networking and Services, 2004. MOBIQUITOUS 2004. The First Annual International Conference on (August 22--26, 2004). 194--202. DOI= http://dx.doi.org/10.1109/MOBIQ.2004.1331726

[2]

Bröring, A., Jürrens, E. H., Jirka, S., and Stasch, C. 2009. "Development of Sensor Web Applications with Open Source Software," in OpenSoruce GIS 2009, University of Nottingham (Suchith Anand, 2009)

[3]

Gomez, L., and Laube, A. 2009. Ontological Middleware for Dynamic Wireless Sensor Data Processing. In Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (SENSORCOMM '09). IEEE Computer Society, Washington, DC, USA, 145--151. DOI=http://dx.doi.org/10.1109/SENSORCOMM.2009.121

Digital Library

[4]

Gruber, T. R. 1993. A translation approach to portable ontology specifications. Knowledge Acquisition. 5, 2 (June 1993), 199--220. DOI= http://dx.doi.org/10.1006/knac.1993.1008

Digital Library

[5]

Hadim, S., and Mohamed, N. 2006. Middleware: Middleware Challenges and Approaches for Wireless Sensor Networks. Distributed Systems Online, IEEE. 7, 3 (March 2006), 1--23. DOI=http://dx.doi.org/10.1109/MDSO.2006.19

Digital Library

[6]

Jang, W., Healy, W.M., and Skibniewski, M.J. 2008. Wireless sensor networks as part of a web-based building environmental monitoring system. Automation in Construction. 17, 6 (August 2008), 729--736. DOI= http://dx.doi.org/10.1016/j.autcon.2008.02.001

[7]

Kim, J.H., Kwon, H., Kim, D.H., Kwak, H.Y., and Lee, S.J. 2008. Building a Service-Oriented Ontology for Wireless Sensor Networks. In Proceedings of the Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008) (ICIS '08). IEEE Computer Society, Washington, DC, USA, 649--654. DOI= http://dx.doi.org/10.1109/ICIS.2008.100

Digital Library

[8]

Levis, P., and Culler, D. 2002. Maté: A tiny virtual machine for sensor networks. SIGOPS Oper. Syst. Rev. 36, 5 (October 2002), 85--95. DOI=http://doi.acm.org/10.1145/635508.605407

Digital Library

[9]

Liu, T., and Martonosi, M. 2003. Impala: a middleware system for managing autonomic, parallel sensor systems. SIGPLAN Not. 38, 10 (June 2003), 107--118. DOI=http://doi.acm.org/10.1145/966049.781516

Digital Library

[10]

Liu, J., Zhao, F. 2005. Towards semantic services for sensor-rich information systems. Broadband Networks, 2005. BroadNets 2005. 2nd International Conference on (Boston, MA, USA, October 7--7, 2005). 967--974. DOI= http://dx.doi.org/10.1109/ICBN.2005.1589709

[11]

Madden, S. R., Franklin, M J., Hellerstein, J. M., and Hong, W. 2005. TinyDB: an acquisitional query processing system for sensor networks. ACM Trans. Database Syst. 30, 1 (March 2005), 122--173. DOI=http://doi.acm.org/10.1145/1061318.1061322

Digital Library

[12]

Masri, W., and Mammeri, Z. 2007. Middleware for Wireless Sensor Networks: A Comparative Analysis. Network and Parallel Computing Workshops, 2007. NPC Workshops. IFIP International Conference on (Liaoning, September 18--21, 2007). 349--356. DOI= http://dx.doi.org/10.1109/NPC.2007.165

Digital Library

[13]

Molla, M. M., and Ahamed, S. I. 2006. A Survey of Middleware for Sensor Network and Challenges. In Proceedings of the 2006 International Conference Workshops on Parallel Processing (Washington, DC, USA, 2006). IEEE Computer Society, 223--228. DOI=http://dx.doi.org/10.1109/ICPPW.2006.18

Digital Library

[14]

Murphy, A. L., and Heinzelman, W. B. 2002. Milan: Middleware Linking Applications and Networks. Technical Report. University of Rochester, Rochester, NY, USA.

Digital Library

[15]

OWL. WWW, available at: http://www.w3.org/2004/OWL/#specs

[16]

PostgreSQL. WWW, available at: http://www.postgresql.org/

[17]

Protégé. WWW, available at: http://protege.stanford.edu/

[18]

Ramos, M. L., Leguay, J., and Conan, V. 2007. Designing a Novel SOA Architecture for Security and Surveillance WSNs with COTS. Mobile Adhoc and Sensor Systems, 2007. MASS 2007. IEEE International Conference on (Pisa, October 8--11, 2007). 1--6. DOI= http://dx.doi.org/10.1109/MOBHOC.2007.4428703

[19]

Simon, D., Cifuentes, C., Cleal, D., Daniels, J., and White, D. 2006. Java#8482; on the bare metal of wireless sensor devices: the Squawk Java virtual machine. In Proceedings of the 2nd international conference on Virtual execution environments (VEE '06). ACM, New York, NY, USA, 78--88. DOI=http://doi.acm.org/10.1145/1134760.1134773

Digital Library

[20]

Sharman, R., Kishore, R., and Ramesh, R. 2007. Using Ontologies in the Semantic Web: A Survey. Ontologies: A Handbook of Principles, Concepts and Applications in Information Systems (Integrated Series in Information Systems). Springer-Verlag, New York, 2007, 79--113, DOI= http://dx.doi.org/10.1007/978-0-387-37022-4_4

[21]

Souto, E., Guimarães, G., Vasconcelos, G., Vieira, M., Rosa, N., Ferraz, C., and Kelner, J. 2005. Mires: a publish/subscribe middleware for sensor networks. Personal Ubiquitous Comput. 10, 1 (December 2005), 37--44. DOI=http://dx.doi.org/10.1007/s00779-005-0038-3

Digital Library

[22]

SunSpot. WWW, available at: http://www.sunspotworld.com

[23]

SWRL. WWW, available at: http://www.w3.org/Submission/SWRL/

[24]

Terfloth, K., Güneş, M., and Schiller, J. H. 2009. Middleware for Wireless Sensor Networks: The Comfortable Way of Application Development. Guide to Wireless Sensor Networks, Springer, London, 2009, 583--606. DOI=http://dx.doi.org/10.1007/978-1-84882-218-4_23

[25]

The Basic SunSPOT Ontology, available at: http://informatika.ftn.uns.ac.rs/SinisaNikolic?action=AttachFile&do=get&target=SunspotBasicModel.owl

[26]

The Open Geospatial Consortium. WWW, available at: http://www.opengeospatial.org/

[27]

TinyOS Project. WWW, available at: http://www.tinyos.net/http://www.tinyos.net

Cited By

Savić GSegedinac MKonjović ZVidaković MDutina R(2023)Towards a Domain-Neutral Platform for Sustainable Digital Twin DevelopmentSustainability10.3390/su15181361215:18(13612)Online publication date: 12-Sep-2023
https://doi.org/10.3390/su151813612
Seydoux NDrira KHernandez NMonteil T(2018)A Distributed Scalable Approach for Rule Processing: Computing in the Fog for the SWoT2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)10.1109/WI.2018.0-100(112-119)Online publication date: Dec-2018
https://doi.org/10.1109/WI.2018.0-100
Nachabe LGirod-Genet MEl Hassan B(2015)Unified Data Model for Wireless Sensor NetworkIEEE Sensors Journal10.1109/JSEN.2015.239395115:7(3657-3667)Online publication date: Jul-2015
https://doi.org/10.1109/JSEN.2015.2393951

Index Terms

Semantic web based architecture for managing hardware heterogeneity in wireless sensor network
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
2. Networks
  1. Network types
    1. Mobile networks
    2. Wireless access networks

Recommendations

Heterogeneity consideration in wireless sensor networks routing algorithms: a review

Wireless sensor networks (WSNs) are resource-constrained networks with limited battery power, computation abilities and communication capabilities at the sensor node level. A long-standing need in the area is to reduce energy consumption of the WSN ...
Efficient multilevel clustering for large-scale heterogeneous wireless sensor networks
ICCCS '11: Proceedings of the 2011 International Conference on Communication, Computing & Security

Wireless sensor networks (WSNs) do not always have sensor nodes of same type. In other words, WSNs are not always homogeneous, but some sensor nodes of higher energy can be used to prolong the lifetime and reliability of WSNs. Heterogeneous wireless ...
Cognitive radio-based clustering for opportunistic shared spectrum access to enhance lifetime of wireless sensor network

In recent times, Cognitive radio (CR)-based wireless sensor networks (WSNs) have been widely used for opportunistic access of the shared spectrum. In WSNs, deployment of sensor nodes (SN) may be random, or it may follow an optimized approach-based upon ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

WIMS '11: Proceedings of the International Conference on Web Intelligence, Mining and Semantics

May 2011

563 pages

ISBN:9781450301480

DOI:10.1145/1988688

Program Chair:
Rajendra Akerkar
Western Norway Research Institute, Norway

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 May 2011

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Ministry of Education, Science and Technological Development

Conference

WIMS '11

WIMS '11: International Conference on Web Intelligence, Mining

May 25 - 27, 2011

Sogndal, Norway

Acceptance Rates

Overall Acceptance Rate 140 of 278 submissions, 50%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
194
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 09 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Savić GSegedinac MKonjović ZVidaković MDutina R(2023)Towards a Domain-Neutral Platform for Sustainable Digital Twin DevelopmentSustainability10.3390/su15181361215:18(13612)Online publication date: 12-Sep-2023
https://doi.org/10.3390/su151813612
Seydoux NDrira KHernandez NMonteil T(2018)A Distributed Scalable Approach for Rule Processing: Computing in the Fog for the SWoT2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)10.1109/WI.2018.0-100(112-119)Online publication date: Dec-2018
https://doi.org/10.1109/WI.2018.0-100
Nachabe LGirod-Genet MEl Hassan B(2015)Unified Data Model for Wireless Sensor NetworkIEEE Sensors Journal10.1109/JSEN.2015.239395115:7(3657-3667)Online publication date: Jul-2015
https://doi.org/10.1109/JSEN.2015.2393951

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents