Abstract
Technological advances in miniaturization and wireless networking have enabled the utilization of distributed wireless sensor networks (WSN) in many applications. WSNs often use clustering as a means of achieving scalable and efficient communications. Cluster head nodes are of increased importance in these network topologies because they are both communication and coordination hubs. Much of the research into maximizing WSN longevity and efficiency focuses on dynamically clustering the network according to the residual energy contained within each node. This is a result of the commonly held assumption that battery depletion is the primary cause of node failure. In this work, we consider that there are applications in which threats may significantly impact node survival. In order to cope with these applications, we present a threat-aware clustering algorithm, extending the Hybrid Energy Efficient Distributed clustering algorithm (HEED) that minimizes the exposure of cluster heads to threats in the network environment. Simulation results indicate that our extended threat-aware HEED, or t-HEED, improves both the longevity and energy efficiency of a WSN while incurring minimal additional overhead. Our research demonstrates and motivates the need for a general framework for adaptive context-aware clustering in WSNs.
Chapter PDF
Similar content being viewed by others
References
A. A. Abbasi and M. Younis, “A survey on clustering algorithms for wireless sensor networks.” vol. 30: Butterworth-Heinemann, 2007, pp. 2826-2841.
O. Younis and S. Fahmy, “HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks,” vol. 3, pp. 366-379, 2004.
S. Yi, J. Heo, Y. Cho, and J. Hong, “PEACH: Power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks.” vol. 30: Butterworth-Heinemann, 2007, pp. 2842-2852.
W.-T. Su, K.-M. Chang, and Y.-H. Kuo, “eHIP: An energy-efficient hybrid intrusion prohibition system for cluster-based wireless sensor networks.” vol. 51: Elsevier North- Holland, Inc., 2007, pp. 1151-1168.
I. Stojmenovic, M. Seddigh, and J. Zunic, “Dominating sets and neighbor elimination-based broad-casting algorithms in wireless networks,” IEEE Transactions on Parallel and Distributed Systems, 13(1): 2002, pp.14–25.
F. Bouhafs, M. Merabti, and H. Mokhtar, “A semantic clustering routing protocol for wireless sensor networks,” Consumer Communications and Networking Conference, IEEE Computer Society, 2006, pp. 351– 355.
F. Siegemund, “A context-aware communication platform for smart objects.” Pervasive, Elsevier, 2004, pp.69–86.
M. Strohbach and H. Gellersen, “Smart clustering - networking smart objects based on their physical relationships,” Proceedings of the 5th IEEE Int’l Workshop on Networked Appliances, IEEE Computer Society, 2002, pp. 151– 155.
R.M Perianu, C. Lombriser, P. Havinga, J Scholten, G. Tröster, “Tandem: A Context-Aware Method for Spontaneous Clustering of Dynamic Wireless Sensor Nodes,” Internet of Things, Int’l Conf. for Industry and Academia, March 2008.
M. Younis, W. Youssef, M. Eltoweissy, and S. Olariu, “Safety- and QoS-Aware Management of Heterogeneous Sensor Networks,” Journal of Inter- connection Networks, Vol. 7, No. 1, 2006, pp. 179-193.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 IFIP International Federation for Information Processing
About this paper
Cite this paper
Blace, R.E., Eltoweissy, M., Abd-Almageed, W. (2008). Threat-Aware Clustering in Wireless Sensor Networks. In: Miri, A. (eds) Wireless Sensor and Actor Networks II. WSAN 2008. IFIP – The International Federation for Information Processing, vol 264. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09441-0_1
Download citation
DOI: https://doi.org/10.1007/978-0-387-09441-0_1
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-09440-3
Online ISBN: 978-0-387-09441-0
eBook Packages: Computer ScienceComputer Science (R0)