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Alexios LekidisDepartment of Informatics, Aristotle University of

Thessaloniki

2st International Workshop on Methods and Tools for Rigorous System Design (MeTRiD)

Prague, Czech Republic06 April, 2019

Model-based energy characterization of IoT system design aspects

1

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1)  IntroductiontotheIoTdesignaspects2)  MethodsforenergycharacterizationoftheIoT

designaspects•  Parametersimpactingdesignaspects•  Energyaspectmonitoring

3)  Casestudy:AspectmonitoringinanIntelligentTransportSystem•  Applicationoftheproposedmethod•  Energyestimationsbasedonsystemrequirements

4)  Conclusionandongoingwork

Outline

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1)  IntroductiontotheIoTdesignaspects2)  MethodsforenergycharacterizationoftheIoT

designaspects•  Parametersimpactingdesignaspects•  Energyaspectmonitoring

3)  Casestudy:AspectmonitoringinanIntelligentTransportSystem•  Applicationoftheproposedmethod•  Energyestimationsbasedonsystemrequirements

4)  Conclusionandongoingwork

Outline

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What is really IoT?

BuildingAutomation

ConnectedvehiclesFuturegrid Healthcare

Industry4.0Homeautomation

IoT

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IoTHeterogeneity

Scalability

Lightweighthardware

Automation

ReliabilityDynamicity Latency

sensitive

IoT application characteristics

Low-cost

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Application example: Connected vehicles

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IoT cyber-security: Mirai botnet threat Gaining control

Launching Denial of Service attacks

Vulnerable RSU

Victim

Controlled IoT devices

Malware loader Server

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IoT cyber-security: Vulnerabilities

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Security vs lifetime

Applications

Systemlibraries

Operatingsystem

Library calls System

calls

Drivers

System calls

Hardware

Security 0

50

100

150

200

250

300

350

400

Low Medium High

Life

time

(day

s)

Security

Ø  Challenge: Provide security mechanisms that have minimal impact on do not:

1)  Energy consumption 2)  IoT device performance

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Previous work [Metrid 2018]

Open directions: 1) Parameters centered around connectivity aspects 2) Feedback for enhancements to the application designer?

•  Characterization of scenarios impacting the energy consumption in different modes:

•  Idle device waiting for events (LPM)

•  Calculations/data processing (CPU)

•  Data transmission (Tx) •  Data reception (Rx)

•  Valid bounds for energy consumption and battery lifetime through an energy-aware model

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1)  IntroductiontotheIoTdesignaspects2)  MethodsforenergycharacterizationoftheIoT

designaspects•  Parametersimpactingdesignaspects•  Energyaspectmonitoring

3)  Casestudy:AspectmonitoringinanIntelligentTransportSystem•  Applicationoftheproposedmethod•  Energyestimationsbasedonsystemrequirements

4)  Conclusionandongoingwork

Outline

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Proposed method: Phase 1

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•  BIPmodelsforeveryleveloftheIoTarchitecturewithtwolayers:–  RESTfulApplicationModel(RESTmoduleallocatedtoeverynode)–  ContikiKernelModel(ContikiOS,protocolstack)

Modeling IoT systems in BIP [Wiley SPE, 2018]

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Energy parameter categories

Energyparameters

Connectivity DataProcessing Security

[Metrid2018]

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• Parametersinfluencingtransmit/receivefunctionalitiesderiveintheirmajorityfromthenetworkstack

• GroupingaccordingtothelayersoftheContikistacktheybelong

•  MAClayer•  Applicationlayer•  Physicallayer

Energy parameters: Connectivity [Metrid 2018]

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Energy parameters: Data processing MemorymanagementinIoTdevices:•  Numberofprocessedresources

•  RoutingprotocolusedforroutingthedatatoCloudservers(i.e.reducingrequiredmemory)

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Energy parameters: Data processing MemorymanagementinIoTdevices:•  Numberofprocessedresources

•  RoutingprotocolusedforroutingthedatatoCloudservers(i.e.reducingrequiredmemory)

•  Memoryblockmanagementusingtwotechniques:

•  Heapmemoryallocationthroughmalloc

•  Dynamicblockallocationthroughmmem

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Energy parameters: Security AspectsforportingsecuritymechanismstoIoTdevices:•  Securitylevelrequiredbythesystemrequirements(authentication/authorization,encryptionorboth)

•  SecurityprotocolindicatingthemechanismusedforsecuredataexchangeintheIoTapplication

•  Sessionkeysizeindicatingthelengthofthekeyusedforencryption/decryptionofpackets

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Energy model

ρ1

λTx

ρ2

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Model calibration

Generalized Pareto with: κ = 0.40227; σ =1.6739; µ = 35.105 parameters

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Proposed method: Phase 2

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Energy aspect monitoring: Connectivity

ca:Thelifetimeofadeviceisgreaterthan1week

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Energy aspect monitoring: Security

cb:processingtimeofsecurityoperations<60%oftheoveralldutycycle

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1)  IntroductiontotheIoTdesignaspects2)  MethodsforenergycharacterizationoftheIoT

designaspects•  Parametersimpactingdesignaspects•  Energyaspectmonitoring

3)  Casestudy:AspectmonitoringinanIntelligentTransportSystem•  Applicationoftheproposedmethod•  Energyestimationsbasedonsystemrequirements

4)  Conclusionandongoingwork

Outline

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ITS Application Aim: Environmental condition awareness to different parts of a city according to ETSI EN 302 637-2/3

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Dynamicattribute(applicabletoeachvehicle/RSU) Value

Speed xx(km/h)

SpeedLimit xx(km/h)

Location longitude,latitude

AccelerationControl brakePedalEngaged,gasPedalEngaged,emergencyBrakeEngaged,collisionWarningEngaged,accEngaged,cruiseControlEngaged,speedLimiterEngaged

Laneposition offTheRoad,hardShoulder,outermostDrivingLane,secondLaneFromOutside

DriveDirection Forward/Backward

WeatherCondition Unavailable,fog,smoke,heavySnowfall,heavyRain,heavyHail,lowSunGlare,sandstorms,swarmsOfInsects

Such attributes change between zones

ITS parameters (ETSI EN 302 637-2/3)

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ITS Application deployment Implementation of a lightweight security library that includes:

•  TLS •  DTLS •  IPSec

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ITS Application deployment RPL routes can be monitored through the router or the Zoul client:

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ITS Application: Energy measurements

•  Obtained using powertrace

•  Energy measurements for: •  Zoul servers •  Zoul client •  Orion border router

•  Current and voltage values obtained from the device datasheet

Energy measurements in different modes

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Actual vs estimated energy

256 key size + authentication scheme 128 key size

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•  ΝovelmethodforestimatingtheenergycostforIoTdesignaspects

•  Energymonitoringthroughmodelconditionsthatallowto:–  Verifyifthesystemrequirementsaremet–  Facilitateapplicationdesignbyestimatingthedesignaspects

underwhichtheyaremet•  Case-study:IntelligentTransportSystem(ITS)providingclimate

conditiondatatopassingvehicles•  Requirementsforstrongsecuritymechanismscontradictwith

devicelifetime•  Alternativeestimationsforsecuritymechanismstomeetmodel

conditionsfordevicelifetime

Conclusions

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Perspectives

•  Methodlimitation:requiresextensivetestsforallthecombinationsofIoTdesignaspectsforeachIoTapplication•  Solution:Identifytherelevantdesignaspectsofthe

applicationandtargetonlythose•  Automatearchitecturalchangesbasedonestimation

feedback•  Large-scaletestbedtodemonstratethescalabilityof

theproposedmethod•  Sophisticatedattackstotesttheefficiencyofthe

securitylibraries

ARISTOTLE UNIVERSITY OF THESSALONIKI

Thank you for your attention. Questions?

Further info: alekidis.csd@auth.gr