Modeling and Simulation of Low Power Wireless Sensor Networks Based on Generalized Nets

Abstract

The Wireless Sensor Networks (WSNs) in now days are facing the additional requirement to provide the functionality to collect, analyze and integrate the sensor data, i.e. to acts as intelligent sensor networks, in addition to the typical transmission and routing functions. The energy minimization at a fixed level performance is very important in wireless sensor nodes which are mainly battery powered. Therefore the understanding of the energy consumption characteristics of each sensor node is critical for the design of energy saving monitoring strategies. The Low Power Wireless Sensor Networks (LPWSN) which are a matter of the current research are applied in many domains, such as ecological and environmental monitoring, traffic management, military applications and etc. The right and realistic model and an adequate simulation of these networks is a key step in the design of a reliable sensor networks architecture and can reduce sensitively the development cost and time. This paper develops a model of LPWSN based on Generalized Nets (GNs) to evaluate the energy consumption of Wireless Sensor Nodes. The proposed model factors important components of a typical sensor node, including SoC (System on Chip) microcontrollers with energy-saving features, wireless front-end components, and low power sensor modules. A Markov chain model of the same network with the same input data was realized as a benchmark. Both models were simulated in WSNet simulator and the data after that compared to real low powered wireless sensor node in lab environment. The output experimental results show that the GN model is more flexible and accurate to the real sensor device than the Markov Chain model and provides a scalable simulation platform to study energy-saving strategies in WSNs.