Introduction about Wireless Sensor Network Simulation: Now a day, we are using a lot of applications for communication and sharing knowledge with one another. We all are having mobile phones in our hands these phones are constructed with a lot of sensors. Current day, these sensors are used in whether detection, fire alarms, theft detection, and so on. These kinds of wireless sensors make our life more safety and comfortable. To improve our knowledge about Wireless Sensor Network is mandatory.
“This article helps to provide an idea about entire knowledge about wireless sensor network simulation, Visual sense, WSN Simulation, modeling and simulation of WSN and more information.”
The Simulation of wireless sensor networks represents monitoring environmental or physical conditions with the use of autonomous devices which have a connection with multiple sensors. The main reason for building a wireless sensor network is to improve the design of the wireless network and increase efficiency. If we construct a wireless network we want some fundamentals. That is,
- Sensor nodes with energy consumption
- Sensor channels
- MAC protocol(Media Access Control)
- Ad hoc networking protocol
- Localization strategies.
Define VisualSence:
The visual sense is mainly used to view the wireless sensor network and its structure. It is software that is user-friendly because this is open-source software anybody can use and share the resources of this software.
The visual sense is built based on the Ptolemy II. This kind of platform is used for the embedded and real-time system for the purpose of designing, modeling, and simulations.
The following point denotes the features of VisualSence:
- In some real-time applications are tested over the performance measuring and hardware platforms are must be tested.
- The main feature of this software is to check the feasibility and validity of wireless sensor node simulation and its modeling.
- To develop a new system it’s important to easily develop a model with open resources.
From this above content, we are known about VisualSence software and its features and how it is easy for constructs a model with freely available sources. Then we enter the topic that is Wireless Sensor Networks Simulation. Our experts have full knowledge about this VisualSence software and doing a lot of research topics in wireless sensor network.
Wireless Sensor Network Simulation
If we need to increase the performance of wireless network simulation, using Network simulators is not suitable. Because network simulators are unable to achieve low energy consumption, mobility, and easy hardware model with its hardware tools. When we say simulation is best which the characteristics of the node give mobility access, easy hardware model, low energy consumption. That’s why we say Network Simulator is not suitable for building wireless Network Simulators.
Main Requirements for Wireless Sensor Network Simulation
When we select requirements for WSN simulation it is important to select based on the tools which are used for the simulation process is compulsory. There are,
- For considering mobile elements to check the availability of the tools in that model.
- Those tools are used by a technical and/or scientific community.
- Consider specific aspects like traffic and sensors in the network for the application.
- Check the scalability that is having various abstraction levels and various sizes.
- Customized tools are easy to integrate the data formats like input/output data.
- Open-Source solution:
- Deployment tools are used to avoid the cost of commercial products with the simulation of the kernel with the open-source elements.
- To develop an easy model and availability of model is based on some models. Like,
- Environment models
- Network models
- Power/Energy models
- Mote/Node models.
So, these are the basic concept of wireless network simulation and the requirements of the tools. Then we will discuss VisualSence again here we know more about VisualSence. We already know VisualSence is open source software to give a framework for wireless sensor networks based on Ptolemy II. Let us see more about VisualSence,
VisualSence
Using java in this VisualSence helps to change the base models. Elements sub-classing, to create a Graphical User Interface (GUI) and creation of new actors are possible by using VisualSence software framework.
- The best match framework can be selected for some reasons. The reasons are,
- Various component of the hardware models is easily changed here we represent the hardware like communication, power, sensor and power supply and etc.
- Choose the component based on modular platforms, when we simulate various levels of abstraction levels it is important to increase the flexibility.
- In various domains, simulate the behavior of the model that gives a better capability. The behaviors like,
- Finite state machines
- Continuous-time
- Synchronous dataflow
- Discrete events and etc.
From this topic, we gain more knowledge about VisualSence. We have more number of developing and developed projects based on VisualSence framework. Then we will move on to the next topic that modular platforms for Wireless Sensor Network Simulation.
What are the modular platforms for WSN Simulation?
The advantage of modularity gives permission to classify the functionalities and is also useful for encapsulation on nodes.
- It gives a new model and design for each simulation process because modularity allows the models to design multiple levels in separate ways.
- This is also used to decrease the effort of researches due to the turn opens platform, to prove the multiple concepts and node flexibility.
- This kind of modular platform is having four layers. There are,
- Sensors
- Processing
- Network Communication
- Power supply.
Let us see each model of the layer in the below topic that is modeling and simulating the modular platforms. Finite state machines represent modular platforms and these layers are given the best result for the events in discrete systems w.r.t to wireless sensor network simulation. Let us discuss each layer in the modular framework in a separate manner.
Simulation models in modular platforms
- Sensor: If we consider the sensor layer in modular platforms it can be classified into three subcategories of functions that id acquiring, dead, and Standby.
- Dead: Dead mode of the sensor is also like a no battery message of the node. If a finite state machine has the dead message and it will eliminate the state from the network.
- Acquiring: In this acquiring state, the role of the sensor is to sense the real world and physical message as an input. Then the inputs are going to the processing state of the network for calculating the total consumption. It is based on a number of sensing devices in the model.
- Standby: If the sensor is in low power mode and the decomposing message comes to the finite state machine it will check the acquire state and send back the consumption rate to the power supply model.
- Processing: In the processing model, there are four states are available. That is sensing, Standby, send, and dead.
- Sensing: In this model, the acquired message are sent by the processing layer from the sensor layer and it measures the message. The new consumption rate is dens to the model of power supply from the FSM.
- Dead: Here also when the low power is consumed the network has to be going to the no battery stage.
- Standby: Simulation of low power consumption is done. Then the rate of consumption is sent to the sensing state and also a power supply mode.
- Send: It is the initial model of the communication layer and it waits for the end of the simulation process. This mode depends upon a number of problems in the transmission and the number of messages is traveling to the neighborhood node.
- Communication: It is the most complex layer in a modular platform. It is used to create a route for Zigbee specification and also manages that king of specification. It also manages the rest of the node communications.
- Power supply: Under the power supply layer it can divide two kinds of modes that is Alive and end.
- Alive: In this model, the balance energy is updated when the inputs ports are receiving a message from the other states. If the energy of the node gets zero all nodes should be considered as a dead node and the power supply is denoted as the end state.
- End: From there is no message is received from finite state machines it is said to be no battery mode. All receiving messages from the input layers are also rejected.
These four layers are used to construct a modular platform for wireless sensor networks. We will hope this article is very useful for gaining your knowledge about Wireless Sensor Network Simulation. Our experts have good experience in such kinds of topics and they give a perfect answer for your doubts. For further more clarifications kindly contact us.