Research And Design Of Energy Consumption Model In Wireless Sensor Network

Wireless sensor networks have been widely used in the military, industry, agriculture, medical care etc. since it is autonomous and no need for infrastructure support. Due to its features being very large scale, unattended and vulnerable to the effects of physical environment, there are many restrictions on wireless nodes, such as weak data processing abilities, limited transmission distance, limited energy storage, and the restricted energy is the key point. Therefore, creating energy consumption model of the node to save energy as effectively as possible and prolong the network lifetime has become a popular research topic.To develop an energy consumption model of the node, not only do we analyze the architecture of node in wireless sensor network, the work mechanism of each functional module, and the relationship between all levels in the node, but also study energy consuming characteristics of the modules and the energy-saving strategies in it. Based on this and taking into account the shortcomings of the current energy consumption model, we propose a new and practical energy consumption model for wireless sensor networks, which has considered the energy consumption of each state as well as that of state transition, and the problem for the demarcation of setting time.This article builds the model from the software perspective, and proposes a periodical sleeping mechanism with time determination, which solves the problem that the frequent state transition lead to cost large amounts of energy of the node. For the generality of this model, we develop a matrix model which can be dynamically configured according to different scenarios.In this paper, using simulation results in the NS2 simulation software, we compared the existing energy model and the new one by configuring the physical parameter of a certain processing module and wireless transceiver module. Simulation results show that the new energy consumption model is more efficient in saving energy for the node, and fitter with the real node's energy consumption.