Algorithm for Improved Normalized Residual Energy in Wireless Nanosensor Networks

Abstract

A Wireless sensor framework may be a portrayed with an arrangement of wireless devices which can pass the information collected by a watched field through remote associations. The information is sent by various center points, and along a gateway, the data is related with various frameworks like remote Ethernet. There are five types of WSNs Terrestrial WSNs, Underground WSNs, Underwater WSNs, Multimedia WSNs, mobile WSNs. There are various challenges in WSN like, Power, cost, security, system architecture etc. In the nanotechnology, Remote nanosensor systems (WNSNs) are a substitution age of detecting component systems found in nano scale, which are suppose to be made inside the returning years. Each nanonode is inside the shift of a little too few nano meters in
measure. The nanoscale property of nanonodes opens energizing new applications inside to detecting space. On the other side, nanotechnology is rapidly gaining the importance in our daily lives and Wireless Nanosensor Networks are now attracts researchers. Among various communication strategies, Electromagnetic communication strategy gives many solutions in many applications and it is really important in building wireless Nanosensor Networks. In this paper, we propose the cluster head selection on the basis of node density, so that we can improve the normalized residual energy and reduce average delay. The simulations are performed on MATLAB. The paper show the improvements in normalized residual energy is 35.84% when the node density is 7 node/????????2
and reduce average delay is 16% when node density is 7 node/????????2
.