Energy Conservation in wireless sensor networks

Kshitij Desai, Mayuresh Randive, Animesh Nandanwar

Basic Design• Sensor Network Architecture

InternetSensor

NetworkSink

Architecture of a Sensor Node

• Ref: Energy Conservation in Wireless Sensor Networks – a Survey

Observations

• Communication Sub-system consumes more energy than computation sub-system

• Energy to transmit one bit = Energy for execution 1000 . instructions

• Radio component requires same order of energy for reception, transmission and idle states

• Sensing sub-system might also require significant amount of energy based on the type of sensor node.

Three Main enabling Techniques

• Duty-cycling• Data-Driven approaches • Mobility

Duty-cycling

• Topology Control• Power Management

• Sleep/Wake Protocols• On-demand, scheduled rendezvous and Async

• MAC Protocols with low Duty-cycle• TDMA, Contention-based and hybrid

Data-driven approaches

• Data reduction• In-Network Processing• Data-Compression• Data-prediction

• Stochastic, Time-series Forecasting and algorithmic approaches

• Energy-efficient data acquisition• Adaptive Sampling• Hierarchical Sampling• Model-Driven active sampling

Mobility-based approaches

• Mobile-sink• Mobile-relay

ATPC: Adaptive Transmission Power Control for Wireless

Sensor Networks

Main Points• What is this paper about?

• Power saving for wireless communication• Paper style?

• Empirical study + a little theory work• What is the contribution?

• Study of spatial-temporal impact on communication• Mechanism to adaptively achieve an optimal transmission power

consumption

Motivation

11

TP1

TP2

TP2

Motivation

12

TP1

TP1

T1

T2

The minimum transmission power level to save energy and maintain specified link quality

TP2

T2

Design Goals

• Achieve energy efficiency• The minimum transmission power

• Maintain Link Quality• Reliable links

• In runtime systems, dynamic environments• Spatial impact• Temporal impact

13

Roadmap

Data Analysis

Empirical Observation

Algorithm Design

Algorithm Evaluation

PART 1

PART 2

Part 1-Transmission Power vs. Link Quality• Link Quality Metrics

• RSSI (Received Signal Strength Indication), LQI (Link Quality Indication), and PRR (Packet Reception Ratio)

• Transmission Power Level Index (3~31)• Experiments on Spatial Impact

• 5 pairs of motes, 3 environments• 100 packets at each transmission power level• RSSI/LQI/PRR measured at different distances

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Part 1- Investigation of Spatial Impact

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3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Transmission Power Level Index

RSSI

(dbm

)

2 ft

6 ft

12 ft

18 ft

24 ft

28 ft

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3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

Transmission Power Level Index

RSSI

(dbm

)

3 ft

6 ft

12 ft

18 ft

24 ft

30 ft

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(a) RSSI measured on a grass field

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3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

Transmission Power Level Index

RSSI

(dbm

)

3 ft6 ft

12 ft18 ft24 ft

30 ft

(c) RSSI measured in a parking lot

1. Different shapes at the same distance in different environments

2. Different degree of variation in different environments

3. Approximately linear

(b) RSSI measured in a corridor

Investigation of Temporal Impact

• Experiment on Temporal Impact• In brushwood where human activity is rare, over 72

hours• 9 MicaZ motes in a line, 3 feet apart• A group of 20 packets at each power level every hour

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Transmission Power Level Index

RSSI

(dbm

)

9am 1st Day

10am 1st Day

11am 1st Day

12pm 1st Day

1pm 1st Day

2pm 1st Day

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Transmission Power Level Index

RSSI

(dbm

)

0am 1st Day

8am 1st Day

4pm 1st Day

0am 2nd Day

8am 2nd Day

4pm 2nd Day

1. Vary gradually but noticeably over time2. Approximately parallel

(a) RSSI measured every 8-hour (b) RSSI measured every hour

Part 1- Link Quality Threshold

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Binary link quality thresholdsSlight different in different environments

(a) RSSI Threshold on a grass field

(b) LQI Threshold on a grass field

0

20

40

60

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100

120

-95 -90 -85 -80 -75 -70RSSI (dbm)

PRR

(%)

0

20

40

60

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100

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50 60 70 80 90 100 110LQI (Reading from MicaZ)

PRR

(%)

Part 2- Model Design of ATPC

• Use a linear model to approximate a non-linear correlation

• rssi(tp) = a · tp +b• Least-square

approximation• Dynamic model• a and b vary

from time to time

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Part 2- ATPC Overview

0.4TP+3264

0.8TP+49273

0.5TP+23122

Control ModelPower LevelNodeID

0.4TP+3264

0.8TP+49273

0.5TP+23122

Control ModelPower LevelNodeID

ATPC Table at Node 1

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Initialization Phase: build models from linear approximation

Node 3

Node 5

Node 4

Node 1 Node

2

Transmission Range

Runtime Tuning Phase: pairwise closed loop control

Packet with Transmission Power

Level 12

Notification

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8

Part 2 – Closed Loop Control

Start here

RSSI, LQI and PRR

Part 2- Experiment Setup

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• Current transmission power control algorithms– A node-level non-uniform solution (Non-uniform)– Network-level uniform solutions

» Max transmission power level (Max)» The minimum transmission power level over nodes in a network

that allows them to reach their neighbors (Uniform)• A 72-hour continuous experiment with MicaZ

– A spanning tree of 43 nodes, 24 leaf nodes– Leaf nodes send 32 packets to the base every hour

Part 2- Experimental Setup

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(a) Weather Conditions over 72 Hours

(b) Spanning Tree Topology (c) Experimental Site

Part 2- Packet Reception Ratio

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0.95

1

0 6 12 18 24 30 36 42 48 54 60 66 72

Time (hours)

End-

to-e

nd P

RR

ATPC

Max

Uniform

Non-Uniform

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0 6 12 18 24 30 36 42 48 54 60 66 72Time (hours)

PRR

(%)

Link with StaticTransmissionPowerLink with ATPC

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(a) E2E packet reception ratioMax ~ 100%

ATPC ~ 98.3% Uniform ~ 98.3% Non-Uniform ~

58.8%

(b) PRR at a chosen linkATPC ~ constantly 100%Static transmission power ~ vary from 0% to 100%

Part 2- Transmission Energy Consumption

0.40.45

0.50.550.6

0.65

0.70.750.8

0.85

0.90.95

1

6 12 18 24 30 36 42 48 54 60 66 72

Time (hours)

Rel

ativ

e Tr

ansm

issi

on E

nerg

y C

onsu

mpt

ion

ATPC

Max

Uniform

Non-Uniform

25Max ~ 100% ATPC ~ 58.3% (1% control overhead) Uniform ~ 68.6% Non-Uniform ~ 43.2%

Relative energy consumption

Conclusions and Future Work

• Benefits of ATPC lie in three core aspects:• ATPC maintains above 98% E2E PRR over time• ATPC achieves significant energy savings

• 53.6% of the transmission energy of Max• 78.8% of the transmission energy of Uniform

• ATPC accurately adjusts the transmission power • Adapting to spatial and temporal factors

• Towards reliable and energy-efficient routing

• Spatial reuse for concurrent transmissions26

Questions?

27

Thank you very much!