Collection Tree Protocol Presentation

Collection Tree Protocol

References :- a. Omprakash Gnawali, Rodrigo Fonseca, Kyle Jamieson, David Moss, and Philip Levis, “Collection Tree Protocol”, In Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems (SenSys 2009), Berkeley, CA, USA, November 2009

b. Ugo Colesanti, Silvia Santini, ”The Collection Tree Protocol for the Castalia Wireless Sensor Networks Simulator”, Technical Report No. 729, Department of Computer Science, ETH Zurich, Zurich, Switzerland, June 2011

09/21/2011 1CS 297 - Fall 2011

http://ctp-castalia.googlecode.com/files/colesanti_santinis_2011_ctp-castalia.pdf



2

Collection

• Anycast route to the sink(s)– Used to collect data from the network

to a small number of sinks (roots, base stations)

– Network primitive for other protocols• A distance vector protocol

sink

09/21/2011 CS 297 - Fall 2011

Desired

• Reliability – delivery ratio 90% - 99.99%• Robustness – no tuning required• Efficiency – mimimum # of packets• Hardware independence – without assuming

specific radio chip features.

309/21/2011 CS 297 - Fall 2011

Common causes of poor performance

• Link Dynamics– Fast more agile network, but costly– Slow slower-to-adapt network, but cheap

• Transient Loops– topology repairs happen at the timescale of

control plane maintenance

409/21/2011 CS 297 - Fall 2011

Common Architecture

5

Router

ForwarderLink Estimator

Link Layer

Application

Control Plane Data Plane

FwdTable

09/21/2011 CS 297 - Fall 2011

Prior Work

6

Link Layer


ETX, MT, MultiHopLQI, EAR, LOF, AODV, DSR, BGP, RIP, OSPF, Babel

Flush, RMST, CODA, Fusion,

IFRC, RCRT

09/21/2011 CS 297 - Fall 2011

Wireless Link Dynamics

7

0.9

1s

09/21/2011 CS 297 - Fall 2011

Control and Data Rate Mismatch

• Can lead to poor performance

8

Link Layer


10 pkt/s1 beacon/30s 0 pkt/s1 beacon/s

09/21/2011 CS 297 - Fall 2011

CTP

9

Router

ForwarderLink Estimator

Link Layer

Application


09/21/2011 CS 297 - Fall 2011

CTP Approach

• Enable control and data plane interaction

• Two mechanisms for efficient and agile topology maintenance– Datapath validation– Adaptive beaconing

10

ControlPlane

DataPlane

09/21/2011 CS 297 - Fall 2011

Additional mechanisms

• Re-transmit timers• Hybrid queue• Per Client queueing• Transmit cache for duplicate suppression

1109/21/2011 CS 297 - Fall 2011

Summary of Results

• 90-99.9% delivery ratio– Testbeds, configurations, link layers

• Compared to MultihopLQI– 29% lower data delivery cost– 73% fewer routing beacons– 99.8% lower loop detection latency

• Robust against disruption• Cause for packet loss vary across testbeds

1209/21/2011 CS 297 - Fall 2011

Outline• Collection• Datapath validation• Adaptive beacons• Re-transmit timers• Hybrid queue• Per-client queueing• Transmit cache• Evaluation• Conclusion

1309/21/2011 CS 297 - Fall 2011

Datapath validation

• Use data packets to validate the topology– Inconsistencies– Loops

• Receiver checks for consistency on each hop– Transmitter’s cost is in the header

• Same time-scale as data packets– Validate only when necessary

1409/21/2011 CS 297 - Fall 2011

15

Routing Loops

– Cost does not decrease

D A

B

8.1

4.6

6.3

3.2

5.8

XC

09/21/2011 CS 297 - Fall 2011

Routing Consistency

• Next hop should be closer to the destination• Maintain this consistency criteria on a path

• Inconsistency due to stale state

16

ni ni+1 nk

09/21/2011 CS 297 - Fall 2011

17

Detecting Routing Loops• Datapath validation

– Cost in the packet– Receiver checks

• Inconsistency– Larger cost than

on the packet• On Inconsistency

– Don’t drop the packets– Signal the control plane

D A

B

C 8.1

4.6

6.3

3.2

5.8

X

4.6

6.3

8.1

5.8

4.6 < 6.3?

3.2 < 4.6?

5.8 < 8.1?

4.6<5.8?

4.6

8.1 < 4.6?

09/21/2011 CS 297 - Fall 2011

Outline

• Collection• Datapath validation• Adaptive beacons• Re-transmit timers• Hybrid queue• Per-client queueing• Transmit cache• Evaluations• Conclusion

1809/21/2011 CS 297 - Fall 2011

How Fast to Send Beacons?

• Using a fixed rate beacon interval– Can be too fast– Can be too slow– Agility-efficiency tradeoff

• Agile+Efficient possible?

1909/21/2011 CS 297 - Fall 2011

Routing as Consistency

• Routing as a consistency problem– Costs along a path must be consistent

• Use consistency protocol in routing– Leverage research on consistency protocols– Trickle

2009/21/2011 CS 297 - Fall 2011

Trickle

• Detecting inconsistency– Code propagation: Version number mismatch– Does not work for routing: use path consistency

• Control propagation rate– Start with a small interval– Double the interval up to some max– Reset to the small interval when inconsistent

2109/21/2011 CS 297 - Fall 2011

22

Control Traffic Timing

• Extend Trickle to time routing beacons• Reset the interval

• ETX(receiver) >= ETX(sender) • Significant decrease in gradient• “Pull” bit

TX

09/21/2011 CS 297 - Fall 2011

23

Adaptive Beacon Timing

Infrequent beacons in the long run

~ 8 min

Tutornet

09/21/2011 CS 297 - Fall 2011

Adaptive vs Periodic Beacons

24

Time (mins)

Less overhead compared to 30s-periodic

1.87beacon/s

0.65beacon/s

Tutornet

09/21/2011 CS 297 - Fall 2011

Node Discovery

25

Time (mins)

A new node introduced

Efficient and agile at the same time

Path established in < 1s

Tutornet

09/21/2011 CS 297 - Fall 2011

Outline

• Collection• Datapath validation• Adaptive beacons• Re-transmit timers• Hybrid queue• Per-client queueing• Transmit cache• Evaluation• Conclusion

2609/21/2011 CS 297 - Fall 2011

CTP Routing Frame

2709/21/2011 CS 297 - Fall 2011

CTP Data Frame

2809/21/2011 CS 297 - Fall 2011

Additional mechanisms• Transmit timers

– Prevent self-interference– Depends upon the packet rate

• Per client queueing– Prevents isolation– One-deep packet queue

• Hybrid send queue– Route-through & locally generated traffic– C + F length

• Transmit cache– Origin address, origin sequence number & THL of N most recently

forwarded packets

2909/21/2011 CS 297 - Fall 2011

Experiments

• 12 testbeds• 20-310 nodes• 7 hardware

platforms• 4 radio

technologies• 6 link layers

30

Variations in hardware, software, RF environment, and topology

09/21/2011 CS 297 - Fall 2011

Reliable, Efficient, and Robust

Testbed Delivery RatioWymanpark 0.9999Vinelab 0.9999Tutornet 0.9999NetEye 0.9999Kansei 0.9998Mirage-MicaZ 0.9998Quanto 0.9995Blaze 0.9990Twist-Tmote 0.9929Mirage-Mica2dot 0.9895Twist-eyesIFXv2 0.9836Motelab 0.9607

31

High end-to-end delivery ratio(but not on all the testbeds!)

Retransmit

False ack

09/21/2011 CS 297 - Fall 2011

32


High delivery ratio across time(short experiments can be misleading!)

Tutornet

0.98

5 10 15 20 25 30 35Time (hrs)

09/21/2011 CS 297 - Fall 2011


33

Low data and control cost

Tutornet CTP Noe

09/21/2011 CS 297 - Fall 2011


34

0

0.2

0.4

0.6

0.8

1

CSMA BoX-1s LPP-500ms

Link Layer

Low duty-cycle with low-power MACs

0.028 0.066

Motelab, 1pkt/5min

09/21/2011 CS 297 - Fall 2011


35

Time (mins)

10 out of 56 nodesremoved at t=60 mins

No disruption in packet delivery

Tutornet

09/21/2011 CS 297 - Fall 2011

Nodes reboot every 5 mins

36


Delivery Ratio > 0.99

Routing Beacons

High delivery ratio despite serious network-wide disruption(most loss due to reboot while buffering packet)

~ 5 min

Tutornet

09/21/2011 CS 297 - Fall 2011

CTP Performance Summary

• Reliability– Delivery ratio > 90% in all cases

• Efficiency– Low cost and 5% duty cycle

• Robustness– Functional despite network disruptions

3709/21/2011 CS 297 - Fall 2011

CTP on Castalia

3809/21/2011 CS 297 - Fall 2011

LE header & footer

3909/21/2011 CS 297 - Fall 2011

Conclusion

• Wireless routing benefits from data and control plane interaction

• Lessons applicable to distance vector routing– Datapath validation & adaptive beaconing

4009/21/2011 CS 297 - Fall 2011

Collection Tree Protocol Presentation

Documents