Distributed Monitoring of Mesh Networks

Elizabeth Belding-RoyerMobility Management and Networking (MOMENT) LabDept. of Computer ScienceUniversity of California, Santa Barbara

Joint work with Krishna Ramachandran and Kevin Almeroth

Motivation: Monitoring

crucial for robust network operation benefits to network operators, system designers,

researchers

essential for evolving network technologies critical last piece in the product conception-

design-development-improvement loop helps bridge the gap between the expected

(simulations) and the unexpected (real-world)

The Big Picture Deployment

UCSB 25 node mesh network (NSF WHYNET project)

Monitoring and Measurement (DAMON) UCSB mesh IETF meetings LocustWorld, IV deployments

11,000 AODV nodes in 50+ countries Simulation models

movement models traffic models AODV refinement

The Big Picture Deployment

UCSB 25 node mesh network (NSF WHYNET project)

Monitoring and Measurement (DAMON) UCSB mesh IETF meetings LocustWorld, IV deployments

11,000 AODV nodes in 50+ countries Simulation models

movement models traffic models AODV refinement

Outline

DAMON Design and Architecture DAMON Implementation DAMON@IETF Conclusions

Design Challenges

Device mobility Resource constraints Fluctuating link quality Short-lived network connections

Design Choices: Pervasiveness of Monitoring Solution

Strategy of using a centralized network element fails no hierarchical structure to

mobile networks mobility

Monitoring mobile networks requires pervasive solution nodes participate in

monitoring Amount of pervasiveness

complete coverage strategy limited coverage strategy

Pervasiveness

NetworkState

Pervasiveness tradeoffs

Design Choices: Pervasiveness of Monitoring Solution

Strategy of using a centralized network element fails no hierarchical structure to

mobile networks mobility

Monitoring mobile networks requires pervasive solution nodes participate in

monitoring Amount of pervasiveness

complete coverage strategy limited coverage strategy

Pervasiveness

AnalysisEffort

Pervasiveness tradeoffs

Additional Design Choices

Number of data sinks single sink? multiple sinks?

Temporal property of monitoring information determined by monitoring requirements classifications

time dependent information, e.g. topology information time independent information, e.g. packet logs

require differentiated handling of data

DAMON: Distributed Architecture for MONitoring mobile networks Overview

agents within network collect information information stored at sinkssink auto-discoveryresiliency to sink failures

Architecture

Agents within network send monitoring information to sinks

Sinks emanate periodic beacons facilitates auto-discovery and resiliency to

sink failures

Sink Auto-discovery

beacons contain agent instructions and hop count

agents use hop count to choose primary sink

Sink Auto-discovery Proximity-based

association (hop count)simple, low overheadbut, can lead to uneven

distribution of agents to sinks

Tradeoff between beaconing frequency and sink detection latency

Monitoring Information

Time dependent i.e., energy left on a device,

neighbors typically small in size packaged into time

dependent digests (TDDs) transmitted to sink

frequently unreliable transmission

Time independent i.e., packet logs, daily

traffic statistics typically large in size broken into small-sized

chunks called time independent digests (TIDs)

reliable transmission

Client Framework

Packet Classifier: categorizes packets based on types, dispatches to appropriate packet handler Beacon Listener: handles beacons TDD dispatcher: handles received TDDs Collectors: summarize routing table info or link quality estimates

in TDDs and TIDs

Packet Classifier

Collector1 Collectorn

Beacon Listener

TDD Dispatcher TID Dispatcher

File Server

Digest Classifier

…

Network

Client Framework

Digest Classifier: delivers digests created by Collectors to appropriate module TDD Dispatcher for immediate transmission to sink File Server for TIDs for later delivery to sink

TID Dispatcher: periodically retrieves digests for transmission to sink

Packet Classifier

Collector1 Collectorn

Beacon Listener

TDD Dispatcher TID Dispatcher

File Server

Digest Classifier

…

Network

DAMON Implementation Goals:

monitor ad hoc network behaviormonitor AODV performancemetrics of interest

throughput traffic distribution control packet overhead mobility patterns

Implementations for Linux and Microsoft Windows

DAMON Information Collection

AODV control packet summaries RREQ, RREP, RERR, Hello received packet counters UDP payload and timestamp

Topology data routing table deltas AODV-NEIGHBOR TDDs sent every minute

Data traffic statistics IP source and destination application protocol type packet size

DAMON@IETF 58th IETF Meeting in

Minneapolis, MN, November 9-14, 2003

Deployment goals: validate DAMON design track IETF topology evaluate AODV

performance observe traffic/mobility

patterns AODV Implementation

Linux, Windows (thanks Intel!)

130+ downloads 20+ simultaneous ad hoc

network members

Network configuration complete coverage

strategy one gateway provided

Internet connectivity to ad hoc network users

one sink deployed to collect information

ad hoc network co-located with 23 IETF APs

nodes used tool called PUDL to avoid unidirectional links

PUDL

Periodic Uni-Directional Link detector periodic unicast probes between each

neighbor pair sequence numbers used to measure

reliability under some threshold (40%), link filtered

from AODV

DAMON@IETF: Network Topology

Network Troubleshooting Connectivity problems with gateway reported

during 13:00-15:30 IETF session on November 11th

Node ID % Broadcast Hello

% Unicast Probes

1 91.8 74.1

2 76.26 12.69

3 92.06 36

4 74.73 42.18

5 69.23 54.1

6 95.42 11.4

7 97.85 6.66

Lessons from Connectivity Information

1. No correlation between reception of unicast and broadcast packets

2. Routing protocols should select routes based on how reliably a path delivers unicast packets

3. Relying on thresholds to avoid unidirectional links can eliminate links that are necessary for connectivity

Traffic Distribution

Per Protocol, With Link Filtering Per Protocol, Without Link Filtering

AODV Traffic Distribution

0

10

20

30

40

50

60

RREQ RREP RERR Hello

With LinkFiltering

Without LinkFiltering

Conclusions

Monitoring essential for robust network operation

DAMON overcomes challenges associated with mobile network monitoring

Future work: more DAMON deployments and analysis tools

http://moment.cs.ucsb.edu/DAMON

Funding provided by NSF and Intel Corporation