AODV GUI Implementation in Wireless Sensor Networks Using MATLAB | Optimized Routing Visualization
Project Abstract
In wireless sensor network (WSN), data collecting from the environment and sending that data to be processed and evaluated is the most important issues. Hence performance evaluation and comparison between routing protocols is required because performance of any routing protocol can be changed or very with various parameters such as speed, seed time, pause time, number of node, and traffic scenario (network topology). In this paper routing protocol AODV, AOMDV, DSR and DSDV has been analyzed by comparing the different performance matrices such as packet delivery ratio (PDR), loss packet ratio (LPR), and average end to end delay (Average End to End) with varying pause time and number of node under TCP & CBR connection via network simulator NS2.35 for wireless sensor network.
A wireless sensor network consists of spatially distributed autonomous sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants. The development of wireless sensor networks was motivated by military applications such as battlefield surveillance. They are now used in many industrial and civilian application areas, including industrial process monitoring and control, machine health monitoring, environment and habitat monitoring, healthcare applications, home automation, and traffic control
A smart sensor node is a combination of sensing, processing and communication technologies. The sensing unit senses the change of parameters, signal conditioning circuitry prepares the electrical signals to convert to the digital domain, the sensed analog signal is converted and is used as the input to the application algorithms or processing unit, the memory helps processing of tasks and the transceiver is used for communicating with other sensors or the base stations or sinks in WSN.
Sensors can monitor temperature, pressure, humidity, soil makeup, vehicular movement, noise levels, lighting conditions, the presence or absence of certain kinds of objects or substances, mechanical stress levels on attached objects, and other properties. Their mechanism may be seismic, magnetic, thermal, visual, infrared, acoustic, or radar. A smart sensor is also capable of self-identification and self-diagnosis. The mechanisms of smart sensors work in one of three ways: by a line of sight to the target (such as visual sensors), by proximity to target (such as seismic sensors), and by propagation like a wave with possible bending (such as acoustic sensors)