Hypergossiping: A Generalized Broadcast Strategy for Mobile Ad Hoc Networks

1. Hypergossiping: A Generalized Broadcast Strategy for Mobile Ad Hoc Networks A. Khelil, P.J. Marrón, C. Becker, K. Rothermel

2. Overview • Motivation • Related Work • System Model • Hypergossiping • Evaluation • Conclusion and Future Work

3. Motivation (1) • Ad hoc communication • WLAN, Bluetooth, UMTS (UTRA-TDD) • Mobile Ad Hoc Networks (MANET) • Examples of applications • Vehicle ad hoc network • Rescue scenarios • MANETs may show • significant variation in node spatial distribution • significant variation in node movement • Broadcasting is widely used in MANETs • Flooding is a common approach

4. Motivation (2) • Flooding encounters two main problems: • In dense MANETs: broadcast storms • Collision, contention and redundancy • In sparse MANETs: network partitioning • Flooding reaches only nodes of one partition • Gossiping is probabilistic flooding • Nodes forward messages with a certain probability to all neighbors, using MAC broadcast • Variation in node density  we adapted gossip probability to number of neighbors  reduces broadcast storms • Gossip still reaches only nodes of one partition •  Broadcast repetition strategy is needed

5. Overview • Motivation • Related Work • System Model • Hypergossiping • Partition Join Detection • Rebroadcasting • Evaluation • Conclusion and Future Work

6. Related Work density dense sparse (partitioned) non-partition-aware protocols, e.g. adaptive gossiping low mobile (e.g. pedestrians) scoped flooding Integrated Flooding (IF) negotiation-based protocols mobility plain flooding Goal: a generalized strategy that supports a wide range of densities and mobilities highly mobile (e.g. vehicles) hyper flooding repeat forwarding restrict forwarding

7. + + System Model A • MANET • N mobile nodes populating a fixed area A (density: d=N/A) • Mobility is required to overcome partitioning • Assumptions • Fixed communication range R • Nodes do not need • Location information • Velocity information • Hello beaconing to acquire neighborhood information • Broadcast data is relevant up tolifetime • Source sets the initial lifetime • Nodes decrement lifetime • Messages are uniquely identified by “source.seqNum” R + + + + + + + + +

8. Overview • Motivation • Related Work • System Model • Hypergossiping • Partition Join Detection • Rebroadcasting • Evaluation • Conclusion and Future Work

9. Our Approach: Hyper-Gossiping (HG) • Goal: maximize reachability efficiently within the given max delay (lifetime) • MANET:= set of partitions that split or join over time. • Approach: we combine two strategies • Gossiping for intra-partition forwarding • Broadcast Repetition Gossiping (forwarding) Repetition (rebroadcasting) Gossiping (rebroadcasting)

10. Broadcast Repetition: Basic Idea m1 1 1 m1 2 2 m1 m5 m1 m1 m5 1 m1 1 2 2 2 2 3 3 m1 m1 m5 3 3 m1 3 3 m5 m1 m5 m5 7 7 7 4 4 m5 m1 6 6 7 7 4 4 6 6 m5 m5 4 4 6 6 m5 m1 m5 7 5 m5 5 m5 m5 m1 5 5 m5 MANET is partitioned partition join detection rebroadcasting broadcast repetition

11. Partition Join Detection Heuristic • Nodes maintain a list of the IDs of Last Broadcast packets Received ( LBR) • Nodes share LBRs with neighbors using existing HELLO beacons • Detection heuristic If then partition join is detected • Heuristic parameters • Max LBR list size:maxLBRlength • Max tolerated intersection of LBR lists:IS_threshold A B LBR_own LBR_recv ID1 ID2 .. IDk

12. Rebroadcasting • If a node detects a partition join, it sends the IDs of all (still relevant) received packets • Receiver sends missed packets A B P1 P2 P3 P4 P5 P1 P2 P3 P4 P5 Node A Node B P4 P5 P6 P7 DATA P6 P7 Buffer (node A) time

13. Overview • Motivation • Related Work • System Model • Hypergossiping • Partition Join Detection • Rebroadcasting • Evaluation • Conclusion and Future Work

14. Area 1Km x 1Km Number of nodes N = 50 .. 500 Communication range R = 100 m Bandwidth r = 1 Mbps infinity 650 s 10 Data size 280 Bytes Mobility model Random waypoint Random in [0.75 , 1.25] s - Max speed v in {3, 12.5, 20, 30} m/s - Pause 2 s Simulation runs Buffer_size HELLO beaconing Simulation time Lifetime 600 s Simulation Parameters Wide density range Wide mobility range ns-2 simulator

15. Hypergossiping Reachability • Reachability = number_of_reached_nodes / total_number_of_nodes

16. Hypergossiping MNFR MNFR: Mean Number of Forwards and Rebroadcasts per node and per message

17. Integrated Flooding (IF) • IMAHN project • Integration of • Plain flooding: every node forwards a newly received message once • Scoped flooding: nodes forward a newly received message, only if a certain ratio of neighbors is not covered by the sender • Hyper flooding: Nodes buffer all packets for a fixed time (=60s), and on discovering new neighbor rebroadcast all buffered packets • Switch depending on relative speed Scoped Flooding Plain Flooding Hyper Flooding low_threshold high_threshold relative speed to node‘s neighbors (10 m/s) (25 m/s)

18. Comparison to Integrated Flooding (IF): Reachability • Reachability = number_of_reached_nodes / total_number_of_nodes

19. Comparison to Integrated Flooding (IF): MNFR MNFR: Mean Number of Forwards and Rebroadcasts per node and per message

20. Conclusion and Future Work • Hypergossiping is a generalized broadcast strategy for MANETs • Adaptive gossiping for intra-partition forwarding • Efficient broadcast repetition strategy on partition join • Hypergossiping covers • a wide range of node densities, and • a wide range of node mobility levels • Future Work • Investigate different buffering strategies • Adapt buffering parameters to node mobility

21. Q&A {khelil, marron, becker, rothermel}@informatik.uni-stuttgart.de