Simulation and Optimization of Energy Consumption on WSNs

Due to the reliance on battery, energy consumption of WSNs has always been the most significant concern. In this work, a method which involves the design of a transaction / system-level based SystemC simulation environment for WSNs energy exploration, and the building of a hardware platform for the real world testbed node measurements to calibrate simulation, is therefore employed to guarantee the accuracy of the energy evaluation on WSNs. To accelerate and optimize the evaluation process, a genetic algorithm (GA) based optimization framework is implemented by MATLAB. The optimization framework attached with our SystemC simulation environment can efficiently, automatically and intelligently fine tune thousands of potential solutions to find the most suitable tradeoff between energy consumption and other metrics under multi- scenario / objective conditions. With our designed evaluation tools, elaborate energy consumption of several popular node platform based networks are investigated, and comprehensive energy-saving strategies are also given. Hence, these analysis could help shed some light for developers and researchers who focus on the energy-efficient WSNs design.

Autorentext

Dr. Nanhao Zhu is a technical consultant of communication network designing and planning at GCI Science & Technology Co., LTD. Canton, China. He completed his Ph.D in Wireless Sensor Networks at Ecole Centrale de Lyon, France, in 2013. He also received his M.S. and B.S. degrees from Communication University of China in 2010 and 2008, respectively.