Sensor Networks

Sen, S. S. Narasimhan and K. Deb. Sensor Network Design of Linear Processes Using Genetic Algorithms. Comput Chem Eng 22 385-390 (1998). 

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

Wireless Sensor Networks for Security Issues and Challenges... 

There is a trade-off between energy expenditure and tracking quality in sensor networks [31]. Sensor activation strategies are naive activation in which all the sensors are active, randomized activation in which a random subset of the sensors are active, selective activation in which a subset of the sensors are chosen according to some performance criterion,... 

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-... 

The model and results developed herein give clues that link false alarms to energy efficiency. Enforcing a low false alarm rate to avoid unnecessary response costs implies either a larger data-set (L) and hence a greater battery consumption, or a denser sensor network, which increases the deployment cost. Similar qualitative and/or quantitative inferences about the relationships between various other parameters can also be made. 

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. R. Brooks, C. Griffin, and D. S. Friedlander, Self-organized distributed sensor network entity tracking , International Journal of High Performance Computing Applications, Vol. 16, No. 3, pp. 207-219, August 2002. 

J. Carle and D. Simplot-Ryl, Energy-efficient area monitoring for sensor networks , IEEE Computer, Vol. 37, No. 2, pp. 40-46, February 2004. 

S. S. Dhillon and K. Chakrabarty, Sensor placement for effective coverage and surveillance in distributed sensor networks, in Proceedings of the IEEE Wireless Communications and Networking Conference, New Orleans, USA, March 2003, pp. 1609-1614. 

E. Ertin, J. W. Fisher, and L. C. Potter, Maximum mutual information principle for dynamic sensor query problems , in Proceedings of the 2nd International Workshop on Information Processing in Sensor Networks, Palo Alto, USA, April 2003, pp. 405-416. 

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. 

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. 

H. Wang, K. Yao, G. Pottie, and D. Estrin, Entropy-based sensor selection heuristic for target localization, in Proceedings of the Third Symposium on Information Processing in Sensor Networks, Berkeley, USA, April 2004, pp. 36-45. 

H. Zhang and C.-J. Hou, On deriving the upper bound of a-lifetime for large sensor networks, Technical Report UIUCDCS-R-2004-2410, University of Illinois at Urbana-Champaign, Department of Computer Science, February 2004. 

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