capacity maximization in wireless sensor network using cmax algorithm

E. Ayyammal,M. Saravanan

Published in International Journal of Advanced Research in Computer Networking,Wireless and Mobile Communications

ISSN: 2320-7248          Impact Factor:1.8         Volume:1         Issue:3         Year: 08 November,2013         Pages:70-76

International Journal of Advanced Research in Computer Networking,Wireless and Mobile Communications

Abstract

Wireless sensor network deals with gathering and sending information to observer in network areas. The aim of this paper is to analyze rate and node lifetime using bandwidth. Power and rate mainly depend upon capacity of the sensor networks. An optimization framework is introduced for a multi-hop sensor network topology maximizing the information capacity sent to the sink. Sensor network capacity depends on energy adaptive mechanisms, power-bandwidth control. The capacity optimization problem is defined analytically and practical local schemes are analyzed. The performance of Rmax and node lifetime on total bandwidth is observed. Energy dissipation of the sensor network is analyzed. CMAX algorithm is used for analyzing energy dissipation of the sensor network. Simulation result is given for the relation between data collected from sensors and available capacity when relays operating at full power by varying total bandwidth. Simulation result also show that the performance of rate and node lifetime is based on the capacity and bandwidth.

Kewords

Wireless sensor network, Capacity, Power adaptation, Capacity maximization algorithm.

Reference

[1] O. Akan, O. Karli, and O. Ergul, “Cognitive radio sensor networks,”IEEE Netw., vol. 23, no. 4, pp. 34–40, July 2009. [2] J. Mitola and G. Maguire, “Cognitive radio: making software radios more personal,” IEEE Pers. Commun., vol. 6, no. 4, pp. 13–18, 1999. [3] F. Digham, “Joint power and channel allocation for cognitive radios,” in Proc. 2008 IEEE WCNC, pp. 882–887. [4] S. Byun, I. Balasingham, and X. Liang, “Dynamic spectrum allocation in wireless cognitive sensor networks: improving fairness and energy efficiency,” in Proc. 2008 IEEE VTC, pp. 1–5. [5] S. Gao, L. Qian, D. Vaman, and Q. Qu, “Energy efficient adaptive modulation in wireless cognitive radio sensor networks,” in Proc. 2007 IEEE ICC, pp. 3980–3986. [6] S. Gao, L. Qian, and D. Vaman, “Distributed energy efficient spectrum access in wireless cognitive radio sensor networks,” in Proc. 2008 IEEE WCNC, pp. 1442–47. [7] X. Li, D. Wang, J. McNair, and J. Chen, “Residual energy aware channel assignment in cognitive radio sensor networks,” in Proc. 2011 IEEE Wireless Commun. Netw. Conf., pp. 398–403. [8] H. Zhang, Z. Zhang, X. Chen, and R. Yin, “Energy efficient joint source and channel sensing in cognitive radio sensor networks,” in Proc. 2011 IEEE Int. Conf. Commun., pp. 1–6.