Cognitive networks works on the basis of their knowledge base. All the gathered and learned information from the previous decisions, actions plans and the end results for the certain activity. It follows recursive loop to achieve the tasks assigned. We can say that it has artificial intelligence merged inside. The main advantage of the cognitive network is the trouble shooting .Immediate data can be seen and there are minimal chance of network failures in cognitive networks because it forms a collaboration chain while working with the seven layers of OSI Model. They are typically us din the real time simulation networks such as artificial intelligence and automotive automation. it also provides services an help in the processing of the other networking elements belonging to the cognitive network.
The concept of cognitive networks emerged in 2005 by the famous Thomas and Mackenzie. This was the advanced and modified version of the old knowledge base theories given by some of the earliest researchers in the networking field. Different research methods provide different results and concept of the knowledge base. People started looking into the idea of cognitive networks in the midst of 20th century.
Role of Prasad and Balamuralidhar
Prasad and Balamuralidhar two famous Indian researchers gave an important turn to the new important statement. They stated that the presiding nature of the networking elements by all the occurring events is essential or the cognitive networks for adapting according to the situation and previous end results. With the passage of the very concept of plane knowledge bas returned into the cross layered designed which can be implemented at every layer of the OSI model. This was quite big achievement in the world of computer networking .it was finally concluded that two main things are required for cognitive networks knowledge base.
- A clear knowledge representation with obvious networking homogeneity and heterogeneity. This statement is essential for the cognitive networks t become the device in all types of networks especially self operated networks.
- For proceeding the processing with the previous knowledge. Cognition loop is there which is formed by utilizing the effective techniques of artificial intelligence integrate din a single circuits or device for taking accurate decisions, creating plans and making the desired results.
In the coming years cognitive networks would be experiencing great advancements and growth. Because all the peripheral and accessories are getting converted into artificially intelligent device which are able to take right decisions at given time.
Cognitive Networks – Introduction
Data networks are in known every where in the world of technology and periodic advancement are implemented to enhance the productivity of existing networking techniques and technologies. Cognitive networks in short CN are the new type of networks specifically designed by the evolved researches to overcome the existing network problems. Cognitive networks are not same a cognitive radio .Its a broader term that completes all seven layers of OSI model. But cognitive radios only cover 1 and 2 layer of OSI model. Cognitive networks are defined by different scientists and researchers according to the perception and conceptual background. In authors point of view its continuous process which is able for perceiving the networking conditions and can decide according to the situation what to decide ,what to do and how to do. One time consequences lay important affect for the future operations of cognitive networks. Cognitive networks are fit for end top end processing and end point engines where loop for certain functionality is constructed. This is one of that learns from the own experiences from its past plans, decisions and actions implemented.