Doubly Cognitive Architecture Based Cognitive Wireless Sensor Networks
Pages 30 - 35
Abstract
Scarcity of spectrum is increasing not only in cellular communication but also in wireless sensor networks. Adding cognition to the existing wireless sensor network WSN infrastructure has helped. As sensor nodes in WSN are limited with constraints like power, efforts are required to increase the lifetime and other performance measures of the network. In this article, the authors propose Doubly Cognitive WSN, which works by progressively allocating the sensing resources only to the most promising areas of the spectrum and is based on pattern analysis and learning. As the load of sensing resource is reduced significantly, this approach saves the energy of the nodes and reduces the sensing time dramatically. The proposed method can be enhanced by periodic pattern analysis to review the strategy of sensing. Finally the ongoing research work and contribution on cognitive wireless sensor networks in Communication Research Centre IIIT-H is discussed.
References
[1]
Akyildiz, I. F., Lee, W.-Y., Vuran, M. C.,&Mohanty, S. 2006. Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey. International Journal of Computer and Telecommunications Networking, 5013, 2127-2159.
[2]
Baldo, N.,&Zorzi, M. 2007, January. Fuzzy logic for cross-layer optimization in cognitive radio networks. In Proceedings of the 4th IEEE Consumer Communications and Networking Conference pp. 1128-1133.
[3]
Cavalcanti, D., Das, S., Wang, J.,&Challapali, K. 2008. Cognitive radio based wireless sensor networks. In Proceedings of the 17th International Conference on Computer Communications and Networks pp. 1-6.
[4]
Fehske, A., Gaeddert, J.,&Reed, J. H. 2005. A new approach to signal classification using spectral correlation and neural networks. In Proceedings of the First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks pp. 144-150.
[5]
Fette, B. 2006. Cognitive radio technology. Oxford, UK: Newnes.
[6]
Gilboa, I.,&Schmeidler, D. 2001. A theory of case-based decisions. Cambridge, UK: Cambridge University Press.
[7]
Harrold, T. J., Faris, P. C.,&Beach, M. A. 2008, September 18. Distributed spectrum detection algorithms for cognitive radio. In Proceedings of the IET Seminar on Cognitive Radio and Software Defined Radios: Technologies and Techniques pp. 1-5.
[8]
Kanal, L. N.,&Sastry, A. R. K. 1978. Models for channels with memory and their applications to error control. Proceedings of the IEEE, 667, 724-744.
[9]
Le, B., Rondeau, T. W., Maldonado, D., Scaperoth, D.,&Bostian, C. W. 2006. Signal recognition for cognitive radios. In Proceedings of the Software Defined Radio Forum Technical Conference.
[10]
Mahmoud, Q. 2007. Cognitive networks: Towards self-aware networks. New York, NY: Wiley-Interscience.
[11]
Raghavendra, C. S. 2007. Wireless sensor networks. New York, NY: Springer.
[12]
Rondeau, T. W.,&Bostian, C. W. 2009. Artificial intelligence in wireless communications. Boston, MA: Artech House.
[13]
Rondeau, T. W., Le, B., Rieser, C. J.,&Bostian, C. W. 2004. Cognitive radios with genetic algorithms: Intelligent control of software defined radios. In Proceedings of the Software Defined Radio Forum Technical Conference pp. 3-8.
[14]
Sohraby, K., Minoli, D.,&Znati, T. F. 2007. Wireless sensor networks: Technology, protocols, and applications. New York, NY: Wiley-Interscience.
- Doubly Cognitive Architecture Based Cognitive Wireless Sensor Networks
Recommendations
Conflict-Free Opportunistic Centralized Time Slot Assignment in Cognitive Radio Sensor Networks
HPCC '14: Proceedings of the 2014 IEEE Intl Conf on High Performance Computing and Communications, 2014 IEEE 6th Intl Symp on Cyberspace Safety and Security, 2014 IEEE 11th Intl Conf on Embedded Software and Syst (HPCC,CSS,ICESS)The unlicensed spectrum bands become overcrowded causing an increased level of interference for current wireless sensor nodes. Cognitive Radio Sensor Networks (CRSNs) overcome this problem by allowing sensor nodes to access opportunistically the ...
Cognitive Radio Sensor Networks: Challenges and Application Areas
IPAC '15: Proceedings of the International Conference on Intelligent Information Processing, Security and Advanced CommunicationWireless Sensor Networks (WSNs) are a class of technology represented with a set of sensor nodes. The main objective of these nodes is to collect data and monitor an environment's events. The basic tasks a node can handle are sensing data (humidity, ...
NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey
Today's wireless networks are characterized by a fixed spectrum assignment policy. However, a large portion of the assigned spectrum is used sporadically and geographical variations in the utilization of assigned spectrum ranges from 15% to 85% with a ...
Comments
Information & Contributors
Information
Published In
Publisher
IGI Global
United States
Publication History
Published: 01 April 2011
Author Tags
Qualifiers
- Article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 09 Nov 2024
Other Metrics
Citations
View Options
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.
Sign in