Energy Efficient Access Selection Algorithm using Cognitive Wireless Sensor Networks

Spectrum sensing is a key feature of a cognitive wireless sensor network, as it helps to minimise unwanted interference between licenced and unlicensed users, as well as identify spectrum utilization for better spectrum use. Reducing the power consumption is one of the key factor to increases the lifetime in cognitive wireless sensor network. The proposed method viz. Access Selection algorithm (ASA) and RRDLA protocol sense the highest residual energy node among several nodes and requests for the best route to enable the data transfer. In parallel, distributed learning automation protocol used in access selection algorithm improves the signal strength, finds the best path with enhanced network life time along with minimum energy consumption. The simulated results using the proposed method demonstrate high network life time.