Trade-off between Efficiency and Robustness Doctoral Colloqium @ - - PowerPoint PPT Presentation

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Sep 06, 2022 469 likes •682 views

Institute of Operating Systems and Computer Networks E ffi ciency E ffi ciency vs Robustness = Trade-o ff Robustness Energy Budget Trade-off between Efficiency and Robustness Doctoral Colloqium @ SenSys18, Shenzhen Robert Hartung,

SLIDE 1

Energy Budget Efficiency Robustness

Efficiency Trade-off Robustness vs =

Trade-off between Efficiency and Robustness

Doctoral Colloqium @ SenSys’18, Shenzhen

Robert Hartung, 2018-11-04 Institute of Operating Systems and Computer Networks

SLIDE 2

Typical application

Sense data Transmit/Receive data

Robust if

... all packets arrive at the sink within deadline ... all nodes are alive during lifetime of network

Efficient if

... there are few re-transmissions ... there are no collisions

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SLIDE 3

Typical application

Sense data Transmit/Receive data

Robust if

... all packets arrive at the sink within deadline ... all nodes are alive during lifetime of network

Efficient if

... there are few re-transmissions ... there are no collisions BUT: We can either be robust or efficient

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SLIDE 4

Challenge 1: Energy constrained

Batteries

Lifetime estimation (before deployment) State-of-Charge (SoC) estimation (after deployment)

Energy Harvesting

Reliability / Predictability

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SLIDE 5

Challenge 2: Environment’s influence

Batteries

Temperature affects both

– Available energy (voltage changes) – SoC estimation

Energy Harvesting

Depends directly on environment, e.g. sun intensity

Node

Communication (e.g. losing packets at higher temperatures)

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SLIDE 6

Challenge 2: Environment’s influence

Batteries

Temperature affects both

– Available energy (voltage changes) – SoC estimation

Energy Harvesting

Depends directly on environment, e.g. sun intensity

Node

Communication (e.g. losing packets at higher temperatures)

Network performance depends on these challenges!

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SLIDE 7

REAP: Robust and Effcient networks due to Adaption of Parameters

IdealVolting Under Volting Energy Measurement

(temp inv.)

Sensors Radio Transceiver

Temperature Humidity Pressure Node

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SLIDE 8

REAP: Robust and Effcient networks due to Adaption of Parameters

IdealVolting Under Volting Energy Measurement

(temp inv.)

Sensors Radio Transceiver

Temperature Humidity Pressure Node

Reliability

(PRR, Retrans.)

Energy

(Cons., Batt., Harv.)

RF Channel

(LQI, RSSI)

Context (Sensors, Channel, TX Power, ...)

State

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SLIDE 9

REAP: Robust and Effcient networks due to Adaption of Parameters

IdealVolting Under Volting Energy Measurement

(temp inv.)

Sensors Radio Transceiver

Temperature Humidity Pressure Node

Reliability

(PRR, Retrans.)

Energy

(Cons., Batt., Harv.)

RF Channel

(LQI, RSSI)

Context (Sensors, Channel, TX Power, ...)

State

Rating

A B C D E F G

Robert Hartung Trade-off between Efficiency and Robustness Seite 5

SLIDE 10

REAP: Robust and Effcient networks due to Adaption of Parameters

IdealVolting Under Volting Energy Measurement

(temp inv.)

Sensors Radio Transceiver

Temperature Humidity Pressure Node

Reliability

(PRR, Retrans.)

Energy

(Cons., Batt., Harv.)

RF Channel

(LQI, RSSI)

Context (Sensors, Channel, TX Power, ...)

State

Rating

A B C D E F G Strategies Save Energy Robustness Tradeoff ... Optimize / Strategy Energy Reliability

Robert Hartung Trade-off between Efficiency and Robustness Seite 5

SLIDE 11

REAP: Robust and Effcient networks due to Adaption of Parameters

Parameters

IdealVolting Under Volting Energy Measurement

(temp inv.)

Sensors Radio Transceiver

Temperature Humidity Pressure Node

Reliability

(PRR, Retrans.)

Energy

(Cons., Batt., Harv.)

RF Channel

(LQI, RSSI)

Context (Sensors, Channel, TX Power, ...)

State

Rating

A B C D E F G Strategies Save Energy Robustness Tradeoff ... Optimize / Strategy Energy Reliability OS Tasks Scheduler Network/Transport Layer RPL µDTN

Robert Hartung Trade-off between Efficiency and Robustness Seite 5

SLIDE 12

Node

Under Volting

Run below specific operating voltage

IdealVolting1

Under Volting at higher temperatures Saves up to 30% of energy

1IdealVolting – Reliable Undervolting on Wireless Sensor Nodes, Kulau et. al, ACM Transactions on Sensor

Networks (TOSN), 2016

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SLIDE 13

State

Model

Unique to each node Build model on node itself

Depends on many parameters Constrained in size and computing power available Additional energy

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SLIDE 14

Rating

Node rates itself in relation to other neighbors Different strategy depending on rating

Change duty cycle Use alternative path

Rating is be shared with neighbors

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SLIDE 15

Strategy

Send data if deadline is too close (prefer robustness) Reduce sensing frequency if energy is low/critical (prefer efficiency) Delay sending packets to more suitable time slot (e.g. warmer)

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SLIDE 16

Routing

E Q A M P I S J K T H C

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SLIDE 17

Routing

E Q A M P I S J K T H C

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SLIDE 18

Routing

E Q A M P I S J K T H C Develop a RPL OF that choses parent node based on parameters / link rating

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SLIDE 19

Conclusion

Trade-off between efficiency and robustness: Depends on a lot of parameters, e.g.

Environmental influences Energy source Neighbors and network topology Application

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