Transcript Distributed Monitoring of Mesh Networks

Distributed Monitoring
of Mesh Networks
Elizabeth Belding-Royer
Mobility Management and Networking (MOMENT) Lab
Dept. of Computer Science
University 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
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essential for evolving network technologies
critical last piece in the product conceptiondesign-development-improvement loop
helps bridge the gap between the expected
(simulations) and the unexpected (real-world)
The Big Picture
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Deployment
 UCSB
25 node mesh network (NSF WHYNET
project)
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Monitoring and Measurement (DAMON)
 UCSB
mesh
 IETF meetings
 LocustWorld, IV deployments
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11,000 AODV nodes in 50+ countries
Simulation models
 movement models
 traffic models
 AODV refinement
The Big Picture
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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
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Design Challenges
Device mobility
 Resource constraints
 Fluctuating link quality
 Short-lived network connections
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Design Choices: Pervasiveness of
Monitoring Solution
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Strategy of using a
centralized network element
Network
fails
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Monitoring mobile networks
requires pervasive solution
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no hierarchical structure to
mobile networks
mobility
nodes participate in
monitoring
Amount of pervasiveness
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complete coverage strategy
limited coverage strategy
State
Pervasiveness
Pervasiveness
tradeoffs
Design Choices: Pervasiveness of
Monitoring Solution

Strategy of using a
centralized network element
fails
Analysis
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

Monitoring mobile networks
requires pervasive solution


no hierarchical structure to
mobile networks
mobility
nodes participate in
monitoring
Amount of pervasiveness


complete coverage strategy
limited coverage strategy
Effort
Pervasiveness
Pervasiveness
tradeoffs
Additional Design Choices
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Number of data sinks
 single
sink?
 multiple sinks?
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Temporal property of monitoring information
 determined
by monitoring requirements
 classifications
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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
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Overview
 agents
within network collect information
 information stored at sinks
 sink auto-discovery
 resiliency to sink failures
Architecture
Agents within network send monitoring
information to sinks
 Sinks emanate periodic beacons
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 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
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Sink Auto-discovery
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Proximity-based
association (hop count)
 simple,
low overhead
 but, can lead to uneven
distribution of agents to
sinks
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Tradeoff between
beaconing frequency
and sink detection
latency
Monitoring Information
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Time dependent
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i.e., energy left on a device,
neighbors
typically small in size
packaged into time
dependent digests (TDDs)
transmitted to sink
frequently
unreliable transmission
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Time independent
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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
Digest Classifier
Collector1
…
File Server
Collectorn
Beacon Listener
Packet Classifier
TDD Dispatcher
TID Dispatcher
Network
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Packet Classifier: categorizes packets based on types,
dispatches to appropriate packet handler
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Beacon Listener: handles beacons
TDD dispatcher: handles received TDDs
Collectors: summarize routing table info or link quality estimates
in TDDs and TIDs
Client Framework
Digest Classifier
Collector1
…
File Server
Collectorn
Beacon Listener
Packet Classifier
TDD Dispatcher
TID Dispatcher
Network
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Digest Classifier: delivers digests created by Collectors
to appropriate module
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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
DAMON Implementation
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Goals:
 monitor ad hoc network behavior
 monitor AODV performance
 metrics of interest
throughput
 traffic distribution
 control packet overhead
 mobility patterns
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Implementations for Linux and Microsoft
Windows
DAMON Information Collection
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AODV control packet summaries
 RREQ, RREP, RERR, Hello
 received packet counters
 UDP payload and timestamp
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Topology data
 routing table deltas
 AODV-NEIGHBOR
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TDDs sent every minute
Data traffic statistics
 IP source and destination
 application protocol type
 packet size
DAMON@IETF
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58th IETF Meeting in
Minneapolis, MN,
November 9-14, 2003
Deployment goals:
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validate DAMON design
track IETF topology
evaluate AODV
performance
observe traffic/mobility
patterns
AODV Implementation
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Linux, Windows (thanks
Intel!)
130+ downloads
20+ simultaneous ad hoc
network members
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Network configuration
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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
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DAMON@IETF: Network Topology
Network Troubleshooting
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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.
2.
3.
No correlation between reception of
unicast and broadcast packets
Routing protocols should select routes
based on how reliably a path delivers
unicast packets
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
60
50
40
With Link
Filtering
Without Link
Filtering
30
20
10
0
RREQ
RREP
RERR
Hello
Conclusions
Monitoring essential for robust network
operation
 DAMON overcomes challenges
associated with mobile network monitoring
 Future work: more DAMON deployments
and analysis tools
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http://moment.cs.ucsb.edu/DAMON
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Funding provided by NSF and Intel
Corporation