A Fuzzy Content Centric Network Architecture for Real-time Communications in MANETs

1. A Fuzzy Content Centric Network Architecture for Real-time Communications in MANETs NiazMorshedChowdhury Dr. Lewis M. Mackenzie School of Computing Science University of Glasgow

2. Mobile Ad-hoc Networks (MANETs) • MANETs: • Can be formed on the fly • Do not require fixed infrastructure • Node can communicate wirelessly • Practical applications of MANETs include: • Military operation • Disaster recovery • Tactical operation • Conference room

3. Practical Application of MANETs • In most practical applications: • One sender – many receivers • Many senders – many receivers • Effectively makes it… • Group-based communication • Real-time communication • Content sharing system

4. Multi-constraint Problem • Conventional approach • Congestion • Appropriate approach • Congestion • Distance • Mobility • Battery

5. Content Sharing System • Who shares? • A sender node to a group of nodes. • How does it share? • By supplying real-time data to a group of nodes • Who receives? • An interested node. • How does it receive? • By notifying sender node about its interest.

6. Content Sharing System

7. A Different View… • Application • stream of real-time data/contents • Originating node • that starts an application • Sender node • that can supply an application • Local node • that receives an application

8. The way we see it…

9. The way we see it…

10. The way we see it…

11. The way we see it…

12. The way we see it…

13. Running on low power…

14. Gets congested…

15. Moved away…

16. Data Structure • Suitability heap • It holds Sigma for each potential sender • It’s a max-heap • Node-to-application matrix • It keeps track availability of application at each node • Requested-application list • Lists all allocation requested by the local node

17. Calculation of Sigma For Node ‘X’ in relation to ‘Y’ d Fuzzy System c Sigma m p ‘X’ is a potential sender node ‘Y’ is the local node Sigma is a weight

18. Calculation of Sigma: Distance

19. Calculation of Sigma: Congestion

20. Calculation of Sigma: Mobility

21. Calculation of Sigma: Power/Battery Life

22. Rules

23. Calculation of Sigma For Node ‘X’ in relation to ‘Y’ d Fuzzy System c Sigma m p ‘X’ is a potential sender node ‘Y’ is the local node Sigma is a weight

24. Operation • When a local node receives request for an application from the user: • It triggers CC-AODV • CC-AODV sends RREQ for specific contents, instead of specific node (address) • Each node having requested application sends back RREP to the local node • Based on d, c, m and p, local node calculates Sigma for those nodes and inserts into the suitability heap. • Finally local node picks root as its ‘sender node’

25. Maintenance • If any negative change in root-node’s Sigma occurs, • Root node will be pushed down in the suitability heap • Local node will cross-check current status of new root • If new root is found suitable, local node switch receiving content from the old root to new root (we call it hand-off) • A local node, • Can act as sender for other nodes that receives content via it. • Can act as sender upon receiving new request.

26. Moved away…

27. Re-structuring

28. Re-structuring

29. Evaluation • 21 node scenario • Custom-built C++ simulation • Effort • The number of hop a packet needs to travel to reach its destination. • For example, to transfer a segment over a 5 hop path, 5 times effort is required.

30. Performance of Individual Transmission

31. Performance of Conference Communications

32. Frequency of Packets on Hops

33. Future Study • Extending functionalities for VANET (primary) • Disseminating warning and safety information • Introducing Reliability (secondary) • Adding transport functionalities

34. Thank You