1. Presented by Venkat Rajiv Vasireddi Pradeep Ramamoorthy

2. Video Communication  Why is video communication far more challenging, when compared to data communication?  Delay sensitive!  Loss sensitive!  What about video communication over wireless ad hoc networks?  Multicast.

3. Multiple Tree Video Multicast  Basic idea:  Split the video into multiple streams using Multiple Descriptive Coding(MDC).  Send each part over different trees, which are considered to be disjoint.  Multiple Disjoint Trees Multicast Routing Protocol (MDTMR).  Two approaches:  Serial MDTMR.  Parallel MNTMR.

4. Multiple Description Coding  3 prediction loops in encoder so the decoder can still track the encoder state when a description is lost.  Use of central predictor and 2 side predictors.  Two descriptions generated by duplicating large DCT Coeff’s in both descriptions and alternating Small one’s between descriptions.  Decoder uses advanced motion compensated temporal interpolation scheme for recovery.  Pairwise correlating transform (PCT) is used to code prediction errors.  Example-Multiple Description Motion Compensation.

5. Multiple Description Coding

6. Tree Connectivity  Tree connectivity level P: P = E[N]/M where, M: total number of receivers and trees.  Given a random topology with n nodes, one sender and m receivers, N is the sum of all receivers connected to each multicast tree.  E[N] is the expected value of N over all topologies.

7. Tree Similarity  Measures the level of disjointness of two trees.  More specifically, similarity S between 2 trees is:  The ratio of the number of shared nodes to the number of middle nodes of the tree with a smaller number of middle nodes.  Disjoint trees  S = zero.  Identical trees  S = one.

8. Serial MDTMR Introduction  Based on the On Demand Multicast Routing Protocol (ODMRP).  Construct two node-disjoint trees.  First, build the shortest-path multicast tree.  Next, construct another tree without the middle nodes of the first tree.  How are packets sent?

9. On Demand Multicast Routing Protocol(ODMRP)  Uses the concept of forwarding groups to forward multicast packets on the shortest path between any member pair – this results in a mesh.  Overcomes the channel overhead and scalability issues of multicast tree based approaches.  Group membership and multicast routes are updated on demand.  Broadcasts Join Requests and Join Tables for mesh construction.  Soft state approach used to maintain multicast group members.

10. Serial MDTMR Tree Construction (Step I)  Source broadcasts a JOIN REQUEST message.  When a node receives this,  it stores the upstream node’s ID and,  rebroadcasts.  When a JOIN REQUEST reaches a receiver, it sends a JOIN ACK to the source, via the reverse shortest path.

11. Serial MDTMR Tree Construction (Step II)  Sender now sends another JOIN REQUEST for the second tree.  Nodes forward only if they’re not a middle node of tree 1.  When the JOIN REQUEST reaches a receiver, it sends a JOIN ACK to the source, via the reverse shortest path in the second tree.

12. Sender Receiver

13. Parallel MNTMR Motivation  Drawbacks of SERIAL MDTMR.  Primary design goals:  Low routing overhead and construction delay.  High tree connectivity.  Low tree similarity.  Distributedness.

14. In a General Single Tree Model…  Source broadcasts a join-query (JQ) message to its neighbors.  Each node forwards its earliest JQ to its neighbors, and so on, till it reaches the receivers.  Each receiver sends a join-reply (JR) message to the sender to construct the tree.

15. Parallel MNTMR Introduction  Aim – construct two nearly disjoint trees in parallel.  Principle – classify nodes randomly into two categories: group 0, or group 1.  However, tree connectivity may be low.  Solution: force every node connected to the sender to forward a JQ message at most once in a JQ process.

16. PARALLEL MNTMR Message Classification  Pure JQ Message – A JQ message forwarded by nodes in the same group.  Mixed JQ Message – A JQ message forwarded by nodes in both groups.  Group-i JQ Message – A JQ message whose last hop is a group-i node.

17. Parallel MNTMR Tree Construction (Step I)  When a node receives a JQ message:  It checks if the message satisfies the JQ message storing condition.  If it does, the message is stored in the node’s JQ message cache.  Else, it is discarded.  Before forwarding the message, the node checks if the message satisfies the JQ message forwarding condition.

18. Parallel MNTMR Message Storing Condition  A JQ message received by node a satisfies the storing condition if:  It is the first JQ message the node receives in this round.  If it satisfies both these conditions:  Number of hops no larger than that of the first JQ message of node a plus one.  JQ message not forwarded by node a.

19. Parallel MNTMR Message Forwarding Condition  A JQ message received at node a satisfies the forwarding condition if:  It has not been forwarded by a.  The last hop was a sender or a group-x node.  If this condition is satisfied, the message is ready to be forwarded.

20. Parallel MNTMR Message Forwarding  A group-x node forwards the earliest received JQ message of the same group immediately.  If there is no message from the same group, it forwards the earliest received JQ message of the other group, after a delay d.  The JQ message is forwarded till it reaches the receiver.

21. Parallel MNTMR Tree Construction (Step II)  When the receiver gets the JQ messages:  It selects one upstream node for each tree – using the upstream node selection rule.  Sends two JR messages via the selected nodes.  This initiates the tree construction process.  When a node receives a JR message:  It too, selects an upstream node.  Forwards the message via the selected node.  Message eventually reaches the sender.

23. Storing Condition? JQ Message N Y Discard JQ Message END Store JQ Message in Cache Forwarding Condition?

24. Store JQ Message in Cache Forwarding Condition? Y Forward JQ Message N 1 st JQ Message? Set JQ-Delay Timer Y

25. Receiver? N END Y 1 st JQ Message?

26. Y Set Receiver Timer N

27. Group-y pure JQ and No JR for tree-y Y Select an Upstream Node Unicast a JR Message to Sender for Tree-y END

28. Parallel MNTMR Upstream Node Selection Rule  Objective – to maximize the disjointness of two trees.  If there exist both group-0 and group-1 messages in the cache, the node selects the earliest received messages from each group as the upstream node for the respective trees.  If only messages from a certain group exist in the cache, the node selects the earliest and second earliest message.  If there is only one element, it is selected as the upstream node for both trees.

29. G-0,1 G-1,2 JQ Message Cache G-1,1 G-0,2 JR from Receiver Node ‘a’Group -0 last hop Tree-0 Group -1 last hop Tree-1

30. G-0,1 G-0,4 JQ Message Cache G-0,2 G-0,3 JR from Receiver Node ‘a’Group -0,1 last hop Tree-0 Group -0,2 last hop Tree-1

31. G-0,1 JQ Message Cache JR from Receiver Node ‘a’Group -0,1 last hop Tree-0 Group -0,1 last hop Tree-1

32. Performance Metrics  Ratio of bad frames.  Number of bad periods.  Normalized packet overhead.  Forwarding efficiency.  Average hops of each packet.  Tree similarity.

33. Simulation Results (I) Ratio of Bad Frames vs. Max. Speed

34. Simulation Results (II) No. of Bad Periods vs. Max. Speed

35. Simulation Results (III) No. of Control Packets/Frame vs. Max. Speed

36. Simulation Results (IV) No. of Forwarded Packets/Received Packet vs. Max. Speed

37. Simulation Results (V) Average Hops of Each Packet vs. Max. Speed

38. Simulation Results (VI) Ratio of Bad Frames vs. Total Cross Traffic

39. Simulation Results (VII) No. of Bad Periods vs. Total Cross Traffic

40. Simulation Results (VIII) Ratio of Bad Frames vs. No. of Receivers

41. Simulation Results (IX) Ratio of Bad Periods vs. Node Density

42. Simulation Results (X) No. of Control Packets/Frame vs. Node Density

43. Simulation Results (XI) Packet Loss Ratio vs. Node Density

44. Simulation Results (XII) Average Delay vs. Node Density

45. Simulation Results (XIII) Average No. of Middle Nodes vs. Node Density

46. What is the Paper Missing?  Assumption: Network is lightly loaded, reasons for packet drop are mobility and poor channel rather than congestion.  Protocol fails when heavily loaded.  Connectivity level has to satisfy  How is node density calculated?  Even with a larger node density, lesser connectivity could happen based on global node placement in the simulation area.

49. What the Paper is Missing? Contd.  What is the probability that both the MDC packet reach the decoder?  No study of the effect of increasing the number of multipaths and MDC’s.  In parallel MNTMR, the primary requirement is the grouping of nodes. Hard to achieve.  Uses only 8 fps. Not the ideal number for video.  Use of tree structure compared to a mesh structure.  Random way point model is used for simulations. Not the ideal model.

50. 50 Classification of Mobility and Mobility Models I-Based on Controllability II-Based on Model Construction

51. 51 Mobility Dimensions and Classification of Synthetic Uncontrolled Mobility Models

52. 52 Mobile devices (laptop, PDAs) Vehicular Networks on Highways Hybrid urban ad hoc network (vehicular, pedestrian)

53. 53 Group Mobility: Multiple Groups

54. Mobility Characteristics from WLANs Simple existing models are very different from the characteristics in WLAN Characterize Prob.(online time fraction > x) On/off activity pattern Skewed location preference Periodic re-appearance

55. Individual users access only a very small portion of APs in the network. On average a user spends more than 95% of time at its top 5 most visited APs. Long-term mobility is highly skewed in terms of time associated with each AP. Users exhibit “on”/”off” behavior that needs to be modeled. Observations: Visited Access Points (APs) Prob.(coverage > x) Fraction of online time associated with the AP CCDF of coverage of users [percentage of visited APs] Average fraction of time a MN associates with APs

56. Clear repetitive patterns of association in wireless network users. Typically, user association patterns show the strongest repetitive pattern at time gap of one day/one week. Repetitive Behavior

57. Thank You!