On the energy efficiency of lossless data compression in wireless sensor networks

Abstract

Principle of democracy as governance is for the people by the people and of the people. People are not the recipient of state framed There has been a lot of research on using less data techniques to minimize the volume and to result ultimately in reducing power consumption. In this page we will study about a way to save data known as Model based clustering which reduces communication flow between nodes to reduce power consumption. The suggested study uses the capacity of mixture-model based group to use both the temporal locality i.e. reuse of specific data and slowly changing properties of the sensing data to framework the sensor network’s traffic. These frameworks can be used by the sensor nodes to the sensed measurements and node to recover the data without data to be fully transferred by a number of sensor nodes. Consequences show that our study contributes to limiting in energy consumption in a resource-limited sensor network