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Broadcast Scheduling in Mobile Ad Hoc Networks ——Related work and our proposed approach By Group 4: Yan Qiao, Yilin Shen, Bharat C. and Zheng Li Presenter:

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Presentation on theme: "Broadcast Scheduling in Mobile Ad Hoc Networks ——Related work and our proposed approach By Group 4: Yan Qiao, Yilin Shen, Bharat C. and Zheng Li Presenter:"— Presentation transcript:

1 Broadcast Scheduling in Mobile Ad Hoc Networks ——Related work and our proposed approach By Group 4: Yan Qiao, Yilin Shen, Bharat C. and Zheng Li Presenter: Zheng Li zhengli@ufl.edu

2 Existing broadcast scheduling approaches for MANET Blind flooding Self/dominant pruning PDP and TDP Forward-node-set-based broadcast

3 Existing broadcast scheduling approaches for MANET Blind flooding Self/dominant pruning PDP and TDP Forward-node-set-based broadcast

4 Existing broadcast scheduling approaches for MANET Blind flooding Self/dominant pruning PDP and TDP Forward-node-set-based broadcast

5 Self Pruning and Dominant Pruning Optimal flooding tree (NP-C) Minimize the cost - the number of transmissions Utilize the neighborhood information exchanged between nodes Nodes keep reporting their existence to neighbors Reference: H. Lim and C. Kim, “Flooding in wireless ad hoc networks.”

6 Self Pruning

7 Dominant Pruning

8 Self Pruning and Dominant Pruning Weakness ◦ Overhead!! “smart” routing  more information needed  increased overhead for transmission Reference: H. Lim and C. Kim, “Flooding in wireless ad hoc networks.”

9 Existing broadcast scheduling approaches for MANET Blind flooding Self/dominant pruning PDP and TDP Forward-node-set-based broadcast

10 Existing broadcast scheduling approaches for MANET Blind flooding Self/dominant pruning TDP and PDP Forward-node-set-based broadcast

11 TDP and PDP Total/partial dominant pruning Utilized the neighborhood information more effectively Further reduced broadcast redundancy Reference: W. Lou and J. Wu “On Reducing Broadcast Redundancy in Ad Hoc Wireless Network”

12 TDP and PDP Work well in the average case, but not good in dense networks Approximation ratio O(n) Can be extended to a clustered network A constant approximation ratio can be achieved

13 Existing broadcast scheduling approaches for MANET Blind flooding Self/dominant pruning PDP and TDP Forward-node-set-based broadcast

14 Process ◦ Clustering and one clusterhead for each cluster ◦ Transmit the message to the clusterhead ◦ Clusterhead choose its forward-node-set to reach the clusterheads within the range. Information of forward clusterheads and forward nodes piggybacked ◦ Nodes retransmit the message or do nothing Reference: J. Wu and W. Lou “Forward-Node-Set-Based Broadcast in Clustered Mobile Ad Hoc Networks.”

15 Forward-node-set-based broadcast Reference: J. Wu and W. Lou “Forward-Node-Set-Based Broadcast in Clustered Mobile Ad Hoc Networks.”

16 Forward-node-set-based broadcast Constant approximation ratio Number of forward nodes relatively stable Dense (all nodes) => sparse (clusterheads) Heavy overhead Forward-clusterhead-set Forward-node-set Clustering by group Reference: J. Wu and W. Lou “Forward-Node-Set-Based Broadcast in Clustered Mobile Ad Hoc Networks.”

17 Existing broadcast scheduling approaches for MANET Blind flooding Self/dominant pruning PDP and TDP Forward-node-set-based broadcast

18 Existing broadcast scheduling approaches for MANET Blind flooding Self/dominant pruning PDP and TDP Forward-node-set-based broadcast

19 Broadcast scheduling in WSN Interference-aware broadcasting Hexagonal tiling Coloring Static WSN … Reference: Ravi Tiwari, Thang N. Dinh, and My T. Thai “On Approximation Algorithms for Interference-Aware Broadcast Scheduling in 2D and 3D Wireless Sensor Networks.”

20 Our approach Hexagonal tilling Coloring to avoid interference Details had been covered … Less assumptions, more realistic ◦ Transmission/interference range Local ◦ Based on local information, group model

21 Compare with FNSB approach Overhead: ◦ FNSB need to keep two lists ◦ Forward clusterheads and forward nodes Latency: ◦ FNSB selects the FNS every time

22 Thank you! Questions?


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