Wireless sensors

Smart dust Researchers at the University of California, Berkeley, have developed smart dust—tiny, intelligent wireless sensors that can communicate with each other, form autonomous networks, reprogram themselves, and monitor almost anything. They have already been tested for various military and nonmilitary applications, but their potential in providing pervasive health care is equally huge [15]. 

Keywords wireless sensor network detection theory Kalman filtering target intrusion detection false alarm. 

Wireless Sensor Networks for Security Issues and Challenges... 

We employ the Neyman-Pearson detector to find the sensing coverage area of the surveillance wireless sensor networks. In order to find the breach path, we apply Dijkstra s shortest path algorithm by us-... 

Wireless sensor networks are prone to failures. Furthermore, the sensor nodes die due to their limited energy resources. Therefore, the failures of sensor nodes must be modeled and incorporated into the breach path calculations in the future. Simulating the reliability of the network throughout the entire life of the wireless sensor network is also required. Lastly, especially for perimeter surveillance applications, obstacles in the environment play a critical role in terms of sensing and must be incorporated into the field model. 

R. Bejar, B. Krishnamachari, C. Gomes, and B. Selman, Distributed constraint satisfaction in a wireless sensor tracking system , in Proceedings of the Workshop on Distributed Constraint Reasoning, International Joint Conference on Artificial Intelligence, Seattle, USA, August 2001. 

T. He, S. Krishnamurthy, J. A. Stankovic, T. Abdelzaher, L. Luo, R. Stoleru, T. Yan and L. Gu, Energy-efficient surveillance system using wireless sensor networks, Proceedings of the Second International Conference on Mobile Systems, Applications, and Services, Boston, USA, June 2004, pp. 270-283. 

J. Liu, P. Cheung, L. Guibas, and F. Zhao, A dual-space approach to tracking and sensor management in wireless sensor networks , in The First A CM International Workshop on Wireless Sensor Networks and Applications, Atlanta, USA, September 2002. 

E. Onur, C. Ersoy and H. Delig, Quality of deployment in surveillance wireless sensor networks , International Journal of Wireless Information Networks, Vol. 12, No. 1, pp. 61-67, January 2005. 

S. Pattern, S. Poduri and B. Krishnamacharie, Energy-quality tradeoffs for target tracking in wireless sensor networks , in Proceedings of Information Processing in Sensor Networks, Palo Alto, USA, April 2003, pp. 32-36. 

N. Patwari and A. O. Hero, Hierarchical censoring for distributed detection in wireless sensor networks , Proceedings of IEEE ICASSP, Vol. 4, Hong Kong, April 2003, pp. 848-851. 

D. Tian and N. D. Georganas, A node scheduling scheme for energy conservation in large wireless sensor networks , Wireless Communications and Mobile Computing, Vol. 3, No. 2, pp. 271-290, May 2003. 

Alan Mainwaring, Joseph Polastre, Robert Szewczyk, David Culler and John Anderson, Wireless Sensor Networks for Habitat Monitoring, in Proceedings of the first ACM international workshop on Wireless sensor networks and applications, Atlanta, Georgia, USA September 28 2002, 88-97. 

The transition from desktop computing to embedded systems is associated with price, power and timing constrains. A special class embedded systems, termed distributed sensor networks (DSN), are characterized by extra requirements small size and sufficient battery lifetime. Distributed sensor networks can be alternatively labeled mobile ad-hoc networks (MANET). While the term DSN is associated with data acquisition applications, MANET emphasizes mobility and the lack of infrastructure. Distributed sensor networks can be scalable to thousands of nodes that cooperatively perform complex tasks. The interaction between the nodes is based on wireless communication [Kah 00, War 01, Hil 02], Wireless sensor networks (WSN) is yet another synonym. 

The nodes of a wireless sensor network can be broken down into two types energy unconstrained network stations and energy constrained sensor nodes. While many applications will only need one network station, the demand for sensor nodes may reach thousands [Bha 02],... 

Gao 00] Gao, Jay Lin, Energy Efficient Routing for Wireless Sensor Networks, Ph.D. theses, University of California, Los Angeles, 2000. 

Hae 05] Haenggi, Martin Opportunities and challenges in wireless sensor networks, in Handbook of Sensor Networks Compact Wireless and Wired Sensing Systems, edited by Mohammad Ilyas and Imad Mahgoub, CRC Press LLC, 2005. 

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