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0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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0.3 Applications for WSN Environment and habitat monitoring Precision Agriculture Indoor climate control Military surveillance Intruder detection Earthquake/volcano prediction Patient vitals monitoring

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Page 1: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

0.1

IT 601: Mobile Computing

Wireless Sensor Network

Prof. Anirudha SahooIIT Bombay

Page 2: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

0.2

Wireless Sensor Networks

• How is it different from traditional wireless network?– for specific application– embedded system with very limited resources

(memory, battery, os)– typical deployment with thousands of nodes– data-centric, individual node’s performance not

important

Page 3: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Applications for WSN

• Environment and habitat monitoring• Precision Agriculture• Indoor climate control• Military surveillance• Intruder detection• Earthquake/volcano prediction• Patient vitals monitoring

Page 4: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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WSN System Challenges• Very Large Scale

– Dense instrumentation– Limited device capability

• Sometimes partial measurements have to be correlated– Limited Access

• Deployed in remote places• Leverage wireless communication to gather information

– Dynamic condition• Environmental condition, event reporting (change in load)• Death of nodes

– Change in topology– Routing protocol

– Operating Systems• Should be scaled down to fit the embedded architecture

Page 5: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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WSN OSs

• Should be scaled down to fit the embedded architecture

• Example OSs– VXWorks, Linux variants, WindowsCE, GeoWorks

• Component based OS– TinyOS from Berekeley

• Concurrency, fine-grained power management, light-weight event scheduler

Page 6: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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MANET vs WSN

Coordinated effort among nodes, data-

centric, mostly low data rate

Individual nodes

important, ID centric, high

data rates

Communication

largeSmallScale

embedded system (with constrained resources)

More powerful, relatively more

resources

Devices (energy)

SpecificGeneralApplication

WSNMANET

Page 7: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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WSN MAC

• Attributes– Collision avoidance– Energy efficiency ------ important– Scalability and adaptability

– Channel utilization– Latency– Throughput ----------- not so important– fairness

Page 8: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Classification of MAC

• Scheduled protocols– Nodes send data in predetermined times

• TDMA, FDMA, CDMA– Contention based protocols

• Nodes compete with probabilistic coordination

– ALOHA, CSMA

Page 9: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Scheduled vs contention-based protocols

Loose or not needed

preciseTime sync

easyDifficultMultihop communicati

on

goodbadscalability

badGoodEnergy efficiency

yesNocollision

Contention-based

protocols

Scheduled protocols

Page 10: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Energy Efficiency in MAC

• Sources of Energy Wastes– Collision– Control packet overhead– Overhearing unnecessary traffic– Idle listening (a major source of energy waste,

consumes 50-100% of the power for receiving)

Page 11: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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S-MAC

• Major Features of S-MAC– Collision avoidance– Periodic listen and sleep– Overhearing avoidance– Adaptive listening– Message passing

Page 12: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Collision Avoidance

• Based on CSMA• Similar to 802.11 DCF

– Physical and virtual carrier sense– Randomized backoff– RTS/CTS for hidden node problem– RTS/CTS/DATA/ACK sequence

Page 13: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Periodic listen and sleep

• Since idle listening consumes lots of energy, S-MAC employs periodic listen and sleep

• Turn off radio while sleeping• Reduce duty cycle to ~10%• Increases latency but decreases energy

consumption

listen listensleep

Page 14: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Periodic listen and sleep

• Neighboring nodes will have the same schedule.• But two nodes who are multihops away, may end up

with different schedules• Border nodes will follow two schedules

– This enables broadcast packets to be sent only once across the two clusters

Page 15: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Overhearing avoidance

• Problem– Nodes receive packets destined for others

• Solution– Sleep when neighbors talk

• Who should sleep?– All immediate neighbors of sender and receiver

• How long to sleep?– The duration field in each packets should be the

duration that the neighbors should sleep

Page 16: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Adaptive Listening

• Reduces latency in multi-hop scenario• Wake up for a short period of time after transmission

from neighbors (if it overheard the corresponding RTS/CTS)– This way, if the node is the next hop node, the node

will be able to send the data immediately instead of waiting for the scheduled listen time

– Reduces latency, but increases duty cycle => more energy consumption

Page 17: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Message Passing• Fragment large messages into small fragments• Have one RTS-CTS exchange for the entire message

– Reserve the medium for the entire message• But ACK is sent by the receiver for every fragment

– If an ACK is not received, only that fragment is retransmitted and the reservation period is extended for one more fragment

• If the entire msg were sent at once, then retransmission would have been costlier

• If only one fragments were sent per RTS-CTS, the control overhead would have been higher and the msg level latency would have been higher

Page 18: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Implementation• Platform

– Mica Motes (UC Berkeley)• 8-bit CPU at 4MHz,• 128KB flash, 4KB RAM• 20Kbps radio at 433MHz

– TinyOS: event-driven (modified stack)• Configurable S-MAC options

– Low duty cycle with adaptive listen– Low duty cycle without adaptive listen– Fully active mode (no periodic sleeping)

Page 19: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Experiment

Ten hop linear topology

Source: S-MAC paper

Page 20: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Energy Consumption vs. msg inter-arrival

Source: S-MAC paper

Page 21: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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Latency vs number of hops

Source: S-MAC paper

Page 22: 0.1 IT 601: Mobile Computing Wireless Sensor Network Prof. Anirudha Sahoo IIT Bombay

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References

• W. Ye, J. Heidemann and D. Estrin, “Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Networks”- IEEE Transactions on Networking, vol. 12, No. 3, June 2004.