Abstract

Transmission Range Adjustment plays an important role in the data transmission within the wireless sensor networks and enhancing the utility of data collected by enabling sensors. Received Signal Strength (RSS) is used to determine the location from which each data packet is obtained. This study proposes the Range adjustment using Received Signal Strength measurement for two ray ground propagation model. Simulation results validate that the proposed Range Adjustment Protocol significantly outperforms the Link-Aware clustering technique with better packet delivery ratio, better energy consumption and improved Accuracy. Wireless Sensor Networks (WSN) are becoming ubiquitous and their application areas are widening by the day. In wireless sensor networks, by adjusting the transmission power based on received signal strength, we can improve the life time of the network.

Keywords:

Clustering, energy efficient, network simulator, received signal strength, routing, wireless sensor network,

References

1. Akyildiz, I.F., W. Su, Y. Sankarasubramaniam and E. Cayirci, 2002. A survey on sensor networks. IEEE Commun. Mag., 40(8): 102-114.
   CrossRef    
2. Banerjee, S. and S. Khuller, 2001. A clustering scheme for hierarchical control in multi-hop wireless networks. Proceeding of the Annual Joint Conference on IEEE Computer and Communication Society, pp: 1028-1037.
   CrossRef    
3. Ford, J., 2001. Telecommunications with MEMS devices: An overview. Proceeding of the 14th Annual Meeting on IEEE Lasers Electro-optical Society, 2: 415-416.
   CrossRef    
4. Gerla, M. and T.C. Tsai, 1995. Multicluster, mobile, multimedia radio network. Wirel. Netw., 1(3): 255-265.
   CrossRef    
5. Jegadeesan, S., M. Sabish, T. Suba Anandhan, K. Sudhakar and D. Syed Ismail, 2013. Energy efficient technique to maximize lifetime of nodes in wireless sensor network. IJECT, 4(2): 122-127.
   
6. Kwon, T.J. and M. Gerla, 2002. Efficient flooding with Passive Clustering (PC) in ad hoc networks. ACM SIGCOMM Comput. Commun. Rev., 32(1): 44-56.
   CrossRef    
7. Lee, K., J. Lee, H. Lee and Y. Shin, 2010. A density and distance based cluster head selection algorithm in sensor networks. Proceeding of the International Conference on Advanced Communication and Technology, pp: 162-165.
   
8. Lin, C.R. and M. Gerla, 1997. Adaptive clustering for mobile wireless networks. IEEE J. Sel. Area. Comm., 15(7): 1265-1275.
   CrossRef    
9. Sheng-Shih, W. and C. Ze-Ping, 2013. LCM: A link-aware clustering mechanism for energy-efficient routing in wireless sensor networks. IEEE Sens. J., 13(2): 728-736.
   CrossRef    
10. Tsai, C.H. and Y.C. Tseng, 2012. A path-connected-cluster wireless sensor network and its formation, addressing and routing protocols. IEEE Sens. J., 12(6): 2135-2144.
    CrossRef    
11. Wei, D., Y. Jin, S. Vural, K. Moessner and R. Tafazolli, 2011. An energy efficient clustering solution for wireless sensor networks. IEEE T. Wirel. Commun., 10(11): 3973-3983.
    CrossRef    
12. Younis, O. and S. Fahmy, 2004. HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE T. Mobile Comput., 3(4): 366-379.
    CrossRef    

Competing interests

The authors have no competing interests.

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The authors have no competing interests.