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A wireless sensor network with a large number of tiny sensor nodes can be used as an effective tool for gathering data in various situations. One of the major issues in wireless sensor networks is developing an energy-efficient routing protocol which has a significant impact on the overall lifetime of the sensor network. In this paper, we propose a novel hierarchical with static clustering routing protocol called Energy-Efficient Protocol with Static Clustering (EEPSC). EEPSC, partitions the network into static clusters, eliminates the overhead of dynamic clustering and utilizes temporary-cluster-heads to distribute the energy load among high-power sensor nodes; thus extends network lifetime. We have conducted simulation-based evaluations to compare the performance of EEPSC against Low-Energy Adaptive Clustering Hierarchy (LEACH). Our experiment results show that EEPSC outperforms LEACH in terms of network lifetime and power consumption minimization.

An efficient iris segmentation method based on analyzing the local entropy characteristic of the iris image, is proposed in this paper and the strength and weaknesses of the method are analyzed for practical purposes. The method shows special strength in providing designers with an adequate degree of freedom in choosing the proper sections of the iris for their application purposes., {"references":["C. E. Shannon, \"A Mathematical Theory of Communication\", Bell System Technical Journal, vol. 27, pp. 379-423, 623-656, July, October,1948.","J. Daugman, \"How Iris Recognition Works\", IEEE Transaction on\ncircuits and systems for video technology, vol. 14, No.1, January 2004.","F. Hao, R. Anderson and J. Daugman, \"Combining Crypto with\nbiometrics effectively\", IEEE transactions on computers, Vol.55, No.9,\nSeptember 2006.","Li.Ma, T. Wang and D.Zhang, \"Efficient Iris Recognition by\nCharacterizing Key Local Variations\" IEEE Trans. On image\nprocessing, vol.13, no. 6, pp. 739-750, 2004.","A. Shojaee Bakhtiari, A. A. Beheshti, B. Zamanlooe, \"Phase\nCongruency Based Image Enhancement Method and Its Application in\nEnhancing Iris Feature Extraction\", Proceedings of Iranian conference\non electrical engineering, 2007.","P. Kovesi, \"Phase Congruency Detects Corners and Edges\", School of\nComputer Science & Software Engineering, The University of Western\nAustralia, November 2003.","W. K. Kong and D.Zhang, \"Accurate Iris Segmentation Based on Novel\nReflection and Eyelash Detection Model\", Proceedings of 2001\nInternational Symposium on Intelligent Multimedia, Video and Speech\nprocessing, May, 2001.","Libor Masek, \"Recognition of Human Iris Patters for Biometric\nIdentification\" University of Western Australia 2003.","P. Kovesi. MATLAB code for calculating phase congruency and phase\nsymmetry asymmetry, April 1996,\nhttp://www.cs.uwa.edu.au/_pk/research/matlabfans/\n[10] Iris Recognition Research Group Center for Biometrics and Security\nResearch National Laboratory of Pattern Recognition, Institute of\nAutomation, Chinese Academy of Sciences. http://www.cbsr.ia.ac.cn"]}