Scalable AODV with Efficient Flooding based on On-Demand (Passive) Clustering

1. Scalable AODV with Efficient Flooding based on On-Demand (Passive) Clustering Yunjung Yi and Mario Gerla University of California, Los Angeles CS Department

2. Motivations • The Lack of Scalability of AODV: • As the number of source-destination pairs increases • Major control overhead of AODV is caused by “Route Query” flood packets • Routing overhead is proportional to the number of route queries • As the given traffic becomes heavy • Heavy routing overhead causes significant effective throughput degradation UCLA CS Dept. WAM Laboratory

3. Proposed Remedy • Reduce routing overhead of AODV using Efficient Flooding (Selective Flooding) • What’s efficient flooding? • Only a subset of nodes (dominating nodes) forwards a Route Query flood packet • In contrast, in blind flooding all nodes relay each packet at most once • How to choose dominant nodes? • Set-Cover problem (NP-complete) • Use heuristics UCLA CS Dept. WAM Laboratory

4. Previous work on Efficient Flooding • Clustering Scheme • Cluster heads and gateways are dominant nodes • Adv. Low computational O/H • Heuristics based on the network topology • Self-Pruning • Based on one-hop neighbors • MPR(MultiPoint Relay) – OLSR • Based on two-hop neighbors’ information • TBRPF • Use a source-tree based on reverse path forwarding • Drawback of above schemes: Background traffic O/H to exchange information between neighbors UCLA CS Dept. WAM Laboratory

5. On-demand (Passive) Clustering • Retains the advantages of clustering scheme • Removes the burden of control O/H • Exploits on-going traffic piggybacked cluster-related information • No clustering with no traffic • Energy efficient • Eliminates cluster setup time (to collect all neighbor information) • Includes efficient and simple gateway selection heuristic • At least two gateways per ordinary node UCLA CS Dept. WAM Laboratory

6. Passive Clustering (2) • “First Declaration Wins” Rule • First declared node can be a CH • Contention Resolution based on Lowest ID wins rule • Eliminates setup latency • Other protocols such as Lowest ID and Highest Degree need a few hello message exchanges to decide a cluster head • Gateway Selection Heuristic • One gateway per each pair of CHs • Two Distributed Gateways allowed for each CH and each ordinary node • Simple but efficient heuristic UCLA CS Dept. WAM Laboratory

7. ClusterHead RREQ (Route Request) Gateway RREP (Route Reply) Ordinary Node Drop AODV with Efficient Flooding based on PC D S UCLA CS Dept. WAM Laboratory

8. Simulation Study • Use GloMoSim • Randomly placed 100 nodes within 1500 x 1000 m2 • Mobility : 2 – 20 m/s with 10 seconds pause time • Transmission Rate : 4pkts/second • Metrics: Delivery ratio & Number of Total Routing Packets UCLA CS Dept. WAM Laboratory

9. Simulation Results UCLA CS Dept. WAM Laboratory

10. Simulation Results (2) UCLA CS Dept. WAM Laboratory

11. Conclusion • Efficient flooding can reduce AODV routing overhead • It improves AODV scalability • PC provides a very efficient flooding platform • PC does not require extra background O/H to construct a cluster. UCLA CS Dept. WAM Laboratory

12. Thank you! Any Questions?