9/25/2000UCLA CSD Gerla, Kwon and

Pei

On Demand Routing in Large Ad Hoc Wireless

Networks

With Passive Clustering

Mario Gerla, Taek Jin Kwon and Guangyu Pei

Computer Science Department

University of California, Los Angeles

Los Angeles, CA, 90095

9/25/2000UCLA CSD Gerla, Kwon and

Pei

Clustering in Ad hoc Networks

A natural way to provide some “structure” in an ad hoc network Better Channel Efficiency(code

diversity) Bandwidth allocation & QoS support Cluster based routing -> scalability Suppress redundant transmissions in

On-Demand Routing

9/25/2000UCLA CSD Gerla, Kwon and

Pei

Example of Clustering

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AODV: flooding O/H

AODV requires flood-search to find and establish routesFlood-search: each node forwards Query pkt (RREQ) to neighborsIf network is “dense” (ie, several nodes within the tx range), this leads to a lot of redundant transmissionsEnergy waste & throughput loss

9/25/2000UCLA CSD Gerla, Kwon and

Pei

Clustering helps On-demand routing

The network is organized in clustersAll nodes in a cluster can communicate directly (one hop) with clusterheadGateways maintain communications between clustersOnly clusterheads and gateways forward search-flood queries Suppress redundant transmissions!

9/25/2000UCLA CSD Gerla, Kwon and

Pei

Example of Clustehead & Gateway Forwarding

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Drawbacks of Conventional Clustering (eg,Least ID #)

Periodic neighbor connectivity monitoring may lead to high O/H

Periodic control traffic not desirable in military covert operations

Unstable behavior of “least ID cluster election” scheme: small move -> large change!

9/25/2000UCLA CSD Gerla, Kwon and

Pei

Passive Clustering

Goals: no monitoring O/H, more stable..

Approach:

(a) No “Active” Control Packets: Cluster state information piggybacked on data packets

(b) Clusters are built only when on-demand routes are opened

(c) Soft state: when data transmissions cease,

time-out clears stale clusters

9/25/2000UCLA CSD Gerla, Kwon and

Pei

Passive Clustering: example

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Assume Node 1 initiates a search flood….

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Passive Clustering

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Passive Clustering

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Clusterhead_ready

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Passive Clustering

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Clusterhead

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Passive Clustering

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Ordinary Node

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Passive Clustering

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Passive Clustering

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Passive Clustering

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Passive Clustering

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Passive Clustering

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Passive Clustering

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Gateway

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Passive Clustering

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Passive Clustering

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Passive Clustering

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Passive Clustering

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Passive Clustering

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Passive Clustering

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Passive Clustering

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Passive Clustering

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Passive Clustering

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Passive Clustering

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Passive Clustering

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Resulting cluster structure.

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Lowest ID Clustering result

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3 isolated clouds – 1, 2, and the rest

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Simulation Environment (GloMoSim)

100 nodes in 1000m x 1000mTransmission range : 150mMobility model: Random Waypoint AODV unicast routingRandom Source/Destination Pairs CBR traffic. 512 bytes per packet, 0.4 packets per

sec

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Pei

Normalized Routing Overhead

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Pei

Mean End-to-End Delay

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Pei

Mean End-to-End Delay

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Pei

Throughput

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Pei

Throughput

9/25/2000UCLA CSD Gerla, Kwon and

Pei

Summary

Passive clustering Realistic, “overhead free” mechanism

First Declaration Wins rule Stable clusterhead election

AODV application Efficient search-flood; higher thoughput;Next: try Passive Clustering on DSR,

ODMRP and other search-flood schemes

Thank You!

9/25/2000UCLA CSD Gerla, Kwon and

Pei

Chain Reaction (contd)

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Chain Reaction (contd)

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Chain Reaction (contd)

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Chain Reaction (contd)

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Passive Clustering

Pros and Cons Little line overhead ↔ Longer Convergence

time Free Neighbor info. ↔ Partial Neighbor Info. Better Structure Easy to Implement Energy Efficiency

Continued ..

9/25/2000UCLA CSD Gerla, Kwon and

Pei

AODV (Ad Hoc On Demand DV) Routing application

AODV version with Hello messagesHello messages exchanged every 1.5 seconds Hello message reduction

No Hello if the node is Ordinary node RREQ, RREP, REER cancel scheduled Hello

Reduced Flooding Ordinary nodes do not forward the RREQ

packets

9/25/2000UCLA CSD Gerla, Kwon and

Pei

Passive Clustering features

Passive clustering with 802.11 Data traffic activated process

Clusterhead election rule – FDW Cluster time out : 2 sec

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Pei

Mean End-to-End Delay

9/25/2000UCLA CSD Gerla, Kwon and

Pei

Chain Reaction set off by motion of node 1

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Final Clusters very different from the initial

ones

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