Here we proposed an Efficient prediction model with a Kalman filter (PKF) combined to reduce the communication cost in Wireless Sensor Networks (WSNs) which provides the guaranteed data quality. Higher energy reductions are achieved by introducing the hardware accelerator that requires fewer resources than previous approaches. The Proposed mechanism shows the Exhaustive experimental results based on datasets from a real WSN application that confirm the various advantages over the previous one. The Primary concern is Energy efficiency in WSNs. KF is combined with a predictor to reduce the communication energy cost for cluster-based WSNs. The technique, called PKF, is suitable for Typical WSN applications use this PKF technique that provides adjustable data quality and tens of pico joule computation cost. From the mathematical point of view, it is challenging to precisely quantify its underlying process.
Volume 11 | 12-Special Issue
Pages: 972-977
DOI: 10.5373/JARDCS/V11SP12/20193302