1. Cognitive Networking ECLT 5820 Presentation 1155071250 & 1155084254
Ricky TSUI & Mike LAU (Group 5)

2. 1. Outline 1. Motivation of Cognitive Network (CN) 2. Definitions
Recapitulation of what we have learn in the lessons
2. Definitions
3. Architecture of CN and Characteristics
4. Failure Handling using cloud technology
5. Summary
6. Q&A Section

4. 1.1 Motivation Objective – to improve QoS Failure handling
system is volatile due to different physical environmental constraints
Communication deadlock may be happened, which affect QoS
Security control - More wireless connection is available, confidential information may be stolen if message pass through bad communication channel
Increase number of mobile device

5. 2. Definitions and Characteristics
Wikipedia- a new type of data network that makes use of cutting edge technology from several research areas (i.e. machine learning, knowledge representation, computer network, network management) to solve some problems current networks are faced with. Thomas et al - A cognitive network has a cognitive process that can perceive current network conditions, and then plan, decide and act on those conditions. The network can learn from these adaptations and use them to make future decisions, all while taking into account end- to-end goals.

6. 3. Framework of CN

7. 3.1 Architecture of 5G era network - Cognitive and cloud Optimized Network proposed by NOKIA

8. 3.2 Characteristics Heterogeneity Openness Security Scalability
Failure Handling
Transparency

9. 4.1 Failure Handling – Hidden and exposed node problem

10. 4.2 Failure Handling – Hidden Terminal Problem

11. 5. Summary
CN is a smart network, which could improve QoS by considering the end-to-end goal of user and selecting the best route
By use of Cognitive Domain (”Cloud )”, the objective of improving QoS, failure handling, enhancing security, etc. can achieved

12. Acknowledgement and source of photos
Lecturer Notes Chapter 9
Wikipedia
Cognitive Networks (Thomas et al, VA)
Cognitive networks (P. Rousu, University of Helsinki)
Solving Hidden Terminal Problem in Cognitive Networks Using Cloud Technologies (Y. B. Reddy, Grambling State University)

13. Q&A Section