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MULTIPLE TREE VIDEO MULTICAST OVER WIRELESS AD HOC NETWORKS Wei Wei and Avideh Zakhor Presented by Venkat Rajiv Vasireddi Pradeep Ramamoorthy

MULTIPLE TREE VIDEO MULTICAST OVER WIRELESS AD HOC NETWORKS Wei Wei and Avideh Zakhor

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MULTIPLE TREE VIDEO MULTICAST OVER WIRELESS AD HOC NETWORKS Wei Wei and Avideh Zakhor. Presented by Venkat Rajiv Vasireddi Pradeep Ramamoorthy. Video Communication. Why is video communication far more challenging, when compared to data communication? Delay sensitive! Loss sensitive! - PowerPoint PPT Presentation

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MULTIPLE TREE VIDEO MULTICAST OVER WIRELESS AD HOC NETWORKSWei Wei and Avideh Zakhor

Presented by Venkat Rajiv VasireddiPradeep Ramamoorthy1Video CommunicationWhy 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.2Multiple Tree Video MulticastBasic 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.3Multiple Description Coding3 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 Coeffs in both descriptions and alternating Small ones 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.

4Multiple Description Coding

5Tree ConnectivityTree connectivity level P:P = E[N]/Mwhere,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.6Tree SimilarityMeasures 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.

7Serial MDTMR IntroductionBased 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?8On 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.

9Serial MDTMR Tree Construction (Step I)Source broadcasts a JOIN REQUEST message.When a node receives this, it stores the upstream nodes ID and,rebroadcasts.When a JOIN REQUEST reaches a receiver, it sends a JOIN ACK to the source, via the reverse shortest path.10Serial MDTMR Tree Construction (Step II)Sender now sends another JOIN REQUEST for the second tree.Nodes forward only if theyre 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.

11SenderReceiverReceiver12Parallel MNTMR MotivationDrawbacks of SERIAL MDTMR.Primary design goals:Low routing overhead and construction delay.High tree connectivity.Low tree similarity.Distributedness.13

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.

14Parallel MNTMR IntroductionAim 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.15PARALLEL MNTMR Message ClassificationPure 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.16Parallel 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 nodes JQ message cache.Else, it is discarded.Before forwarding the message, the node checks if the message satisfies the JQ message forwarding condition.17Parallel MNTMR Message Storing ConditionA 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.

18Parallel MNTMR Message Forwarding ConditionA 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.

19Parallel MNTMR Message ForwardingA 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.

20Parallel 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.

2122Storing Condition?JQ MessageNYDiscard JQ MessageENDStore JQ Message in CacheForwarding Condition?23Store JQ Message in CacheForwarding Condition?YForward JQ MessageN1st JQ Message?Set JQ-Delay TimerY24Receiver?NENDY1st JQ Message?251st JQ Message?YSet Receiver TimerN26Group-y pure JQ and No JR for tree-yYSelect an Upstream NodeUnicast a JR Message to Sender for Tree-yEND27Parallel MNTMR Upstream Node Selection RuleObjective 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.

28G-0,1G-1,2JQ Message CacheG-1,1G-0,2JR from ReceiverNode aGroup -0 last hopTree-0Group -1 last hopTree-129G-0,1G-0,4JQ Message CacheG-0,2G-0,3JR from ReceiverNode aGroup -0 ,1 last hopTree-0Group -0,2 last hopTree-130G-0,1JQ Message CacheJR from ReceiverNode aGroup -0 ,1 last hopTree-0Group -0,1 last hopTree-131Performance MetricsRatio of bad frames.Number of bad periods.Normalized packet overhead.Forwarding efficiency.Average hops of each packet.Tree similarity.

32Simulation Results (I)Ratio of Bad Frames vs. Max. Speed

33Simulation Results (II)No. of Bad Periods vs. Max. Speed

34Simulation Results (III)No. of Control Packets/Frame vs. Max. Speed

35Simulation Results (IV)No. of Forwarded Packets/Received Packet vs. Max. Speed

36Simulation Results (V)Average Hops of Each Packet vs. Max. Speed

37Simulation Results (VI)Ratio of Bad Frames vs. Total Cross Traffic

38Simulation Results (VII)No. of Bad Periods vs. Total Cross Traffic

39Simulation Results (VIII)Ratio of Bad Frames vs. No. of Receivers

40Simulation Results (IX)Ratio of Bad Periods vs. Node Density

41Simulation Results (X)No. of Control Packets/Frame vs. Node Density

42Simulation Results (XI)Packet Loss Ratio vs. Node Density

43Simulation Results (XII)Average Delay vs. Node Density

44Simulation Results (XIII)Average No. of Middle Nodes vs. Node Density

45 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.

4647

48 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 MDCs .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.4950

Classification of Mobility and Mobility ModelsI-Based on ControllabilityII-Based on Model Construction

5051Mobility Dimensions and Classification of Synthetic Uncontrolled Mobility Models

5152

Mobile devices (laptop, PDAs)Vehicular Networks on HighwaysHybrid urban ad hoc network (vehicular, pedestrian)5253 Group Mobility: Multiple Groups53Mobility Characteristics from WLANsSimple existing modelsare very differentfrom the characteristicsin WLAN

CharacterizeProb.(online time fraction > x)

On/off activity pattern

Skewed location preference

Periodic re-appearance54

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 APCCDF of coverage of users[percentage of visited APs]Average fraction of time a MN associates with APs55

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 Behavior56

Thank You! 57

Hybrid

Mobile

Mobility

Static (e.g., sensor networks)

Predictable Mobility

Hybrid

Unpredictable Mobility

Hybrid

Uncontrolled Mobility

Controlled Mobility

Hybrid

Trace-based

Model

Synthetic

Hybrid

Usage pattern

Movement Pattern