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Scalable Team Multicast in Wireless Ad hoc networks Exploiting Coordinated Motion

Scalable Team Multicast in Wireless Ad hoc networks Exploiting Coordinated Motion. Mario Gerla University of California, Los Angeles. Introduction. Many team-oriented operations in MANET scenarios Search and rescue, disaster relief operation, battlefields

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Scalable Team Multicast in Wireless Ad hoc networks Exploiting Coordinated Motion

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  1. Scalable Team Multicast in Wireless Ad hoc networks Exploiting Coordinated Motion Mario Gerla University of California, Los Angeles

  2. Introduction • Many team-oriented operations in MANET scenarios • Search and rescue, disaster relief operation, battlefields • Each team tends to move together (affinity team model)  a chosen node (e.g., landmark) can represent a team • Often, all nodes or none in a team join a multicast group • Affinity team model simplifies mobility handling, and thus allows a scalable multicast protocol design • LANMAR (Landmark ad hoc routing protocol) works well with affinity team model

  3. Introduction (2) • Proposed idea, two-tier team multicast, called M-LANMAR • Unicast tunneling from the sources to the representative of each subscribed team • Flooding within a team • Advantages of M-LANMAR • High reliability via unicast tunneling and flooding • Easy to manage the large networks based on motion affinity model

  4. LANMAR (Landmark Ad Hoc Routing Protocol) –Background • Proactive Routing • Efficient handling affinity team model • Using the notion of landmarks to keep track of logical subnets (teams) • Using two routing schemes • A local proactive routing: within a limited scope, nodes exchange their routing table each other • A long haul distance vector routing: a landmark of each subnet is propagated to the whole network • Routing Tables • Local routing table • Landmark table

  5. local routing Long haul routing subnetAddr1 LM1 node2 subnetAddr2 LM2 node3 subnetAddr3 LM3 node3 LANMAR-Example LM2 LM1 Landmark Logical Subnet LM3 dest node2 Node3 (src) node1 Landmark Table of node1 (subnet_addr, lm_addr, nextHop, …) Local Routing Table of node1 (destAddr, nextHop, …) Node2 Node2 Node3 Node3 …

  6. M-LANMAR(Multicast-enabled LANMAR) • Extension of LANMAR • Proactive scheme • Supporting both unicast and multicast routing with very low extra overhead • Scalable as the network size and number of groups increase • Join MC group: advertising by piggybacking subscribed multicast groups IDs to landmark broadcast packets • Leave MC group: simply not advertising/timeout • The sources can find joined teams in their landmark table

  7. Scope = 2 Flooding Tunneling Scope = 2 Landmark table of source node Flooding subnetAddr1 LM1 node2 MC1 MC1 subnetAddr2 LM4 node3 subnetAddr3 LM2 node3 … LM2 LM1 LM3 Subscribed Teams Source node (MC1) LM4

  8. Simulation • Compared with • ODMRP (On Demand Multicast Routing Protocol) • Flooding • Environments • QualNet 2.9 • Each source generates data in a CBR fashion • Transmission range: 376m, bandwidth 2Mbits • Network size: 6000 x 6000 m2 • Nodes: 1000 nodes into 36 teams • Mobility: 2 m/s with 10 seconds pause time • Following “Reference Point Group Mobility” • Packet size: 512 bytes

  9. Simulation Results – Static Network (1000 nodes, 3teams for each group, 1pkts/sec) Normalized CTRL OH Delivery Ratio Number of MC Groups(#) Number of MC Groups(#) • As the number of multicast groups increases • ODMRP suffers from large control overhead and collisions • M-LANMAR achieves high delivery ratio (by unicast tunneling and flooding)

  10. 1pkt/sec 4pkts/sec ODMRP M-LANMAR FLOOD ODMRP M-LANMAR FLOOD Simulation Results – Mobile Network(1000 nodes, 3teams for each group, 2m/s, 10p)

  11. Simulation Results – Mobile Network(1000 nodes, 3teams for each group, 2m/s, 10p) (2) • As the number of multicast groups increases • With small number of groups, ODMRP outperforms M-LANMAR because of its mesh-based multicast structure (redundant paths); M-LANMAR potentially experiences many link breakages • With large number of groups, flooding suffers due to heavy overhead • With high offered load (right), M-LANMAR outperforms ODMRP (ODMRP suffers from heavy redundant forwarding)

  12. Reliable Multicast Support • Reliable Adaptive Lightweight Multicast (RALM) • Targeting general multicast protocols • NACK-Oriented mechanism • Rate-based congestion control • Send-and-wait mechanism (freeze the sender’s buffer upon receiving a NACK); congestion handling • Round-robin recovery • Sources recover the lost pkts for each NACKER one at a time in a round-robin fashion • Prevent ACK implosion • Combining with M-LANMAR • Only landmarks (say representatives) send feedback (e.g. NACK/ACK) to the source • Prevents unnecessary feedback implosion

  13. Simulation Results with RALM(1000 nodes, 3teams for each group, 2m/s, 10p, 5 multicast groups) –Delivery ratio • Same parameters to • the mobile network • experiment • Increase the offered load (number of pkts/sec) • ODMRP suffers from feedback implosion

  14. Simulation Results with RALM(1000 nodes, 3teams for each group, 2m/s, 10p, 5 multicast groups) –Throughput

  15. Discussions • Possible extensions of M-LANMAR • Efficient resource discovery via content based multicast • Use existing MANET multicast protocols to multicast a packet to all landmarks • Scalable as the number of teams increases • Provide a congestion controlled reliable transport layer like TCP between the sources and the landmarks

  16. Conclusion • Propose a new multicast paradigm • Team multicast • Design M-LANMAR as an example of team multicast • Study the performance of M-LANMAR compared with ODMRP and FLOOD • Flat multicast has scalability limitations • M-LANMAR provides an efficient platform for a reliable and congestion controlled multicast protocol (e.g., TCP) • Apply a reliable transport protocol, RALM over M-LANMAR and ODMRP • M-LANMAR is an efficient platform for a reliable multicast protocol

  17. Thank you Any Questions?

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