ABSTRACT
Networks of specialized, geographically scattered wireless sensors that track and record physical environmental conditions and transmit the collected information to a central point are called wireless sensor networks. They are formed by a large number of wireless sensor nodes. WSNs are capable of measuring environmental factors such as sound, wind, temperature, humidity, and pollution levels. It is difficult to model a WSN analytically because it is complex and infeasible, resulting in simplified analysis and low confidence. Therefore, simulation plays a crucial role in the study of WSNs. It requires a good model built on reliable premises and a suitable framework that facilitates implementation. Simulation results also depend on assumptions about the environment, physical layer, and hardware, which are often too inaccurate to accurately reflect the actual behavior of a WSN, calling into question their validity. However, due to the enormous number of nodes that need to be simulated depending on the application, advanced models have scalability and performance issues. Thus, in modeling WSNs, the trade-off between scalability and accuracy becomes a significant problem. In this chapter, we present several simulation tools for wireless sensor networks that are widely used in the industry.
