Using Manhattan Mobility Model for the Counter-Base Broadcasting protocol in MANETs

1. END’s Talk Using Manhattan Mobility Model for the Counter-Base Broadcasting protocol in MANETs Sara Omar al-Humoud

2. Outline • Introduction • Cbase • Mobility Models • RWP • MMM • Results • Future Direction

3. Research Outline ACBase2 ACBase1 Contribution Related work Probabilistic Deterministic Flooding Broadcasting Introduction Routing Wireless MANET

4. Counter Base Broadcast Scheme • When receiving a message: • counter c is set to keep track of number of duplicate messages received. • Random Assessment Delay (RAD) timer is set. • When the RAD timer expires the counter is tested against a fixed threshold value C, broadcast is inhibited if c > C.

5. Adjusted Counter-based1 Comparison Flow charts between Counter-based Flooding Get the Broadcast ID Get degree n of node X c = 1 Get the Broadcast ID c = 1 Set RAD [0..Tmax] Get the Broadcast ID n < avg • C = c2 • Tmax = Tmax2 • C = c1 • Tmax = Tmax1 Set RAD [0..Tmax] While (RAD) While (RAD) same packet heard same packet heard same packet heard • c = c + 1 • c = c + 1 • End while • End while C < c C < c • Trans packet • drop packet • Trans packet • drop packet • Trans packet • drop packet

6. Adjusted Counter-Based Broadcast Adjusted Counter-Based Broadcast Based on the original counter-based scheme Add the ability to decide the counter and the RAD according to neighbourhood density Neighbourhood density is divided according to the Average number of neighbours into: Density1: Sparse Density2: Dense ACBase1 Scheme Sparse Dense Neighbourhood Density Avg

7. Outline • Introduction • Cbase • Mobility Models • RWP • MMM • Results • Future Direction

8. Mobility Models • Traces • Synthetic Model • Entity • Group Dartmouth MobiLib

9. Random Way Point Mobility Model RWP How it works: • at every instant, a node randomly chooses a destination and moves towards it with a velocity chosen randomly from [0, Vmax], where Vmax is the maximum allowable velocity for every mobile node. 25 nodes

10. Manhattan Mobility Model MMM How it works: • A node is allowed to move along the grid of horizontal and vertical streets on the map. • At an intersection the node can turn left, right or go straight. • P of same street = 0.5 • P of turning left = 0.25 • P of turning right = 0.25 MANHATTAN HOR_STREET_NUM 3 VER_STREET_NUM 3 LANE_NUM 12 25 nodes (3x3 street)

11. Outline • Introduction • Cbase • Mobility Models • RWP • MMM • Results • Future Direction

12. Prameters Simulation parameters

13. Performance metrics Saved Rebroadcast (SRB) (r − t)/r r = number of hosts receiving the broadcast message t = number of hosts that actually transmitted the message. Reachability r/e r = number of hosts receiving the broadcast packet e = number of mobile hosts that are reachable, directly or indirectly, from the source host . Average latency the interval from the time the broadcast was initiated to the time the last host finished its rebroadcasting.

14. Results SRB

15. Results Reachability

16. Results Average Latency

17. Future Directions • MMM • Limiting the number of nodes (cars) in a lane • Building a bigger map (Glasgow cc) • Scripting a mobility map generator • Develop the ACBase2 that calculates the threshold value according to a function of the number of neighbours

18. Questions

19. Introduction Broadcasting Applications • Discovering neighbours • Collecting global information • Addressing • Helping in multicasting and Unicast • Route discovery, route reply • in on-demand routing protocols like DSR, AODV to broadcast control messages. • Conventionally broadcast is done through flooding

20. Introduction Broadcasting Applications • Flooding may lead to • Redundancy x Consume limited bandwidth • Contention x Increase in delay • Collision x High packet loss rate • Broadcast storm problem! f(n) = n2 – 2n + 1

21. Related work Probability-based Rebroadcast with probability P Counter-based Rebroadcast if the node received less than Cth copies of the msg Location-based Rebroadcast if the area within the node’s range that is yet to be covered by the broadcast > Ath Distance-based Rebroadcast if the node did not receive the msg from another node at a distance less than Dth Probabilistic Broadcasting Methods Receiver rebroadcast decision Simple Implementation RD based on instantaneous information from broadcast msgs

22. Related work Reliable Broadcast Self-pruning Scalable broadcasting Dominant Pruning Cluster-based Deterministic Broadcasting Methods Sender rebroadcast decision Elaborate Implementation Rebroadcast decision based on neighbourhood study

23. Related work Counter-based broadcast Adaptive Counter-based broadcast [Tseng2003] Adjusted Counter-Based [Aminu2007] Color-based broadcast [Haddad 2006] Distance-aware counter-based broadcast [Chen 2005] Counter-Based related Broadcasting Methods

24. Questions Is there a realistic mobility model? Obstacle Mobility Model Project 2005 Ns2, GlomoSim the Mobility Management and Networking (MOMENT) Lab, the Networking and Multimedia Systems Lab (NMSL) and the Geometric Computing Lab (GCL). University of Califorrnia at Santa Barbara RealMobGen 2008 Ns2 Dartmouth's and University of Southern California's C. Walsh, A. Doci, and T. Camp, A Call to Arms: It’s Time for REAL Mobility Models, ACM's Mobile Computing and Communications Review, to appear 2008 Towards a better simulation 30

25. Questions Is there a visualisation tool to view network topology? iNSpect Towards a better simulation NS-2 Trace files Mobility files OpenGL animation iNSpect 31

26. Questions How to validate and compare scenarios? SCORES tool (SCenariO characteRizEr for Simulation) Towards a better simulation SCORES Node coverage Num nodes Nw diameter Simulation area Neighbor count Transmission range Foot print … Mobility file topology change rate Delivery ratio, end-to-end delay, throughput, overhead Metamodels 32

27. Questions