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A.U.Th.
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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A.U.Th. 2
1) IntroductiontotheIoTdesignaspects2)
MethodsforenergycharacterizationoftheIoT
designaspects• Parametersimpactingdesignaspects•
Energyaspectmonitoring
3) Casestudy:AspectmonitoringinanIntelligentTransportSystem•
Applicationoftheproposedmethod•
Energyestimationsbasedonsystemrequirements
4) Conclusionandongoingwork
Outline
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A.U.Th. 3
1) IntroductiontotheIoTdesignaspects2)
MethodsforenergycharacterizationoftheIoT
designaspects• Parametersimpactingdesignaspects•
Energyaspectmonitoring
3) Casestudy:AspectmonitoringinanIntelligentTransportSystem•
Applicationoftheproposedmethod•
Energyestimationsbasedonsystemrequirements
4) Conclusionandongoingwork
Outline
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A.U.Th. 4
What is really IoT?
BuildingAutomation
ConnectedvehiclesFuturegrid Healthcare
Industry4.0Homeautomation
IoT
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A.U.Th. 5
IoTHeterogeneity
Scalability
Lightweighthardware
Automation
ReliabilityDynamicity Latency
sensitive
IoT application characteristics
Low-cost
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Application example: Connected vehicles
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A.U.Th. 7
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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A.U.Th. 9
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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A.U.Th. 11
1) IntroductiontotheIoTdesignaspects2)
MethodsforenergycharacterizationoftheIoT
designaspects• Parametersimpactingdesignaspects•
Energyaspectmonitoring
3) Casestudy:AspectmonitoringinanIntelligentTransportSystem•
Applicationoftheproposedmethod•
Energyestimationsbasedonsystemrequirements
4) Conclusionandongoingwork
Outline
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A.U.Th. 12
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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A.U.Th. 14
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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A.U.Th. 17
Energy parameters: Data processing
MemorymanagementinIoTdevices:• Numberofprocessedresources
•
RoutingprotocolusedforroutingthedatatoCloudservers(i.e.reducingrequiredmemory)
• Memoryblockmanagementusingtwotechniques:
• Heapmemoryallocationthroughmalloc
• Dynamicblockallocationthroughmmem
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A.U.Th. 18
Energy parameters: Security
AspectsforportingsecuritymechanismstoIoTdevices:•
Securitylevelrequiredbythesystemrequirements(authentication/authorization,encryptionorboth)
•
SecurityprotocolindicatingthemechanismusedforsecuredataexchangeintheIoTapplication
•
Sessionkeysizeindicatingthelengthofthekeyusedforencryption/decryptionofpackets
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A.U.Th. 19
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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A.U.Th. 24
1) IntroductiontotheIoTdesignaspects2)
MethodsforenergycharacterizationoftheIoT
designaspects• Parametersimpactingdesignaspects•
Energyaspectmonitoring
3) Casestudy:AspectmonitoringinanIntelligentTransportSystem•
Applicationoftheproposedmethod•
Energyestimationsbasedonsystemrequirements
4) Conclusionandongoingwork
Outline
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A.U.Th. 25
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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A.U.Th. 32
Perspectives
•
Methodlimitation:requiresextensivetestsforallthecombinationsofIoTdesignaspectsforeachIoTapplication•
Solution:Identifytherelevantdesignaspectsofthe
applicationandtargetonlythose•
Automatearchitecturalchangesbasedonestimation
feedback• Large-scaletestbedtodemonstratethescalabilityof
theproposedmethod•
Sophisticatedattackstotesttheefficiencyofthe
securitylibraries
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ARISTOTLE UNIVERSITY OF THESSALONIKI
Thank you for your attention. Questions?
Further info: [email protected]
