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Broadcast Scheduling in Broadcast Scheduling in Mobile Ad Hoc NetworksMobile Ad Hoc Networks
——Related work and our proposed approach
By Group 4: Yan Qiao, Yilin Shen, Bharat C. and Zheng Li
Presenter: Zheng Li
Existing broadcast Existing broadcast scheduling approaches for scheduling approaches for
MANETMANET
Blind floodingSelf/dominant pruningPDP and TDPForward-node-set-based
broadcast
Existing broadcast Existing broadcast scheduling approaches for scheduling approaches for
MANETMANET
Blind floodingSelf/dominant pruningPDP and TDPForward-node-set-based
broadcast
Existing broadcast Existing broadcast scheduling approaches for scheduling approaches for
MANETMANET
Blind floodingSelf/dominant pruningPDP and TDPForward-node-set-based
broadcast
Self Pruning and Dominant Self Pruning and Dominant PruningPruning
Optimal flooding tree (NP-C)Minimize the cost - the number of
transmissionsUtilize the neighborhood information
exchanged between nodesNodes keep reporting their
existence to neighbors
Reference:H. Lim and C. Kim, “Flooding in wireless ad hoc networks.”
Self PruningSelf Pruning
Dominant PruningDominant Pruning
Self Pruning and Dominant Self Pruning and Dominant PruningPruning
Weakness◦Overhead!!
“smart” routing more information needed increased overhead for transmission
Reference:H. Lim and C. Kim, “Flooding in wireless ad hoc networks.”
Existing broadcast Existing broadcast scheduling approaches for scheduling approaches for
MANETMANET
Blind floodingSelf/dominant pruningPDP and TDPForward-node-set-based
broadcast
Existing broadcast Existing broadcast scheduling approaches for scheduling approaches for
MANETMANET
Blind floodingSelf/dominant pruningTDP and PDPForward-node-set-based
broadcast
TDP and PDPTDP and PDP
Total/partial dominant pruningUtilized the neighborhood
information more effectivelyFurther reduced broadcast
redundancy
Reference:W. Lou and J. Wu“On Reducing Broadcast Redundancy in Ad Hoc Wireless Network”
TDP and PDPTDP and PDPWork well in the average case, but not
good in dense networksApproximation ratio O(n)Can be extended to a clustered
network A constant approximation ratio can be
achieved
Existing broadcast Existing broadcast scheduling approaches for scheduling approaches for
MANETMANET
Blind floodingSelf/dominant pruningPDP and TDPForward-node-set-based
broadcast
Forward-node-set-based Forward-node-set-based broadcastbroadcastProcess
◦ 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.”
Forward-node-set-based Forward-node-set-based broadcastbroadcast
Reference:J. Wu and W. Lou“Forward-Node-Set-Based Broadcast in Clustered Mobile Ad Hoc Networks.”
Forward-node-set-based Forward-node-set-based broadcastbroadcastConstant approximation ratioNumber of forward nodes relatively stableDense (all nodes) => sparse
(clusterheads)Heavy overhead
Forward-clusterhead-setForward-node-set
Clustering by group
Reference:J. Wu and W. Lou“Forward-Node-Set-Based Broadcast in Clustered Mobile Ad Hoc Networks.”
Existing broadcast Existing broadcast scheduling approaches for scheduling approaches for
MANETMANET
Blind floodingSelf/dominant pruningPDP and TDPForward-node-set-based
broadcast
Existing broadcast Existing broadcast scheduling approaches for scheduling approaches for
MANETMANET
Blind floodingSelf/dominant pruningPDP and TDPForward-node-set-based
broadcast
Broadcast scheduling in Broadcast scheduling in WSNWSNInterference-aware broadcastingHexagonal tilingColoringStatic 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.”
Our approachOur approachHexagonal tillingColoring to avoid interferenceDetails had been covered…Less assumptions, more realistic
◦Transmission/interference rangeLocal
◦Based on local information, group model
Compare with FNSB Compare with FNSB approachapproach
Overhead: ◦FNSB need to keep two lists◦Forward clusterheads and forward
nodesLatency:
◦FNSB selects the FNS every time
Thank you!Thank you!
Questions?Questions?