An Architecture Framework for Experimentations with Self ...
Transcript of An Architecture Framework for Experimentations with Self ...
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CHARLES UNIVERSITY IN PRAGUE
http://d3s.mff.cuni.cz
faculty of mathematics and physics
CHARLES UNIVERSITY IN PRAGUE
http://d3s.mff.cuni.cz
faculty of mathematics and physics
CHARLES UNIVERSITY IN PRAGUE
http://d3s.mff.cuni.cz
faculty of mathematics and physics
An Architecture Framework for Experimentations with Self-
Adaptive Cyber-Physical Systems
Michal KitIlias Gerostathopoulos
Tomas BuresPetr HnetynkaFrantisek Plasil
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Smart Cyber-Physical Systems
• Open-ended: no strict system boundaries
• Decentralized
• Physical world Distribution
Mobility
• Communication WiFi, 3G/4G, but also MANETS, VANETS etc.
How can we endow such systems with self-adaptive and self-organizing capabilities?
2Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
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What is special about smart CPS?
3Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
Self-adaptation in smart CPS is hard... especially when combined with dependability.
• No global state• Dynamic physical structure• Unstable connections: no communication
guarantees• Communication delays: data becomes obsolete• Inherent dynamism stemming from external
uncertainty and openness• Emergent behavior
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Example: E-mobility
POI: WorkTime: 7AM-4PM
POI: CinemaTime: 2PM-4PM
POI: ShoppingTime: 4PM-6PM
POI: ShoppingTime: 4PM-6PM
POI: HomeTime: 6:45PM
POI: HomeTime: 6:30PM
4Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
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5
Systematic Experimentation
To build self-adaptive smart CPS we need to first experiment with different adaptation approaches
An experimentation framework should have:
• Suitable abstractions
Goals, agents/components, component grouping
• Simulation capabilities
Network communication (including ad-hoc networks)
Environment behavior
Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
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DEECo
Component framework for self-adaptive smart CPS
• Suitable abstractionsArchitecture: autonomous components & ensembles
Requirements: invariants
• Simulation capabilitiesNetwork-accurate communication (OMNET++)
Agent-based simulations of the environment (MATSim)
jDEECo: Java-based implementation of DEECo
• Based on internal Java DSL (Java annotations)
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jDEECo Features
7Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
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Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
DEECo – Architecture Abstractions
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Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
DEECo – Architecture Abstractions
(component)Vehicle
schedule
route
…
(component)ParkingLot
position
freePlaces
…
(component)Vehicle
schedule
route
…
(component)ParkingLot
position
freePlaces
…
(component)ParkingLot
position
freePlaces
…
(component)ParkingLot
position
freePlaces
…
(component)ParkingLot
position
freePlaces
…
(component)ParkingLot
position
freePlaces
…
Component
Knowledge
Processes
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Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
DEECo – Architecture AbstractionsEnsemble AvailableParkingLotsCloseToDestination {
v: IVehiclep: IParkingLot
membership : proximity(p.position, v.route) <= DIST_THR
&& p.freePlaces >= FREE_PLACES_THR
knowledge exchange {v.availablePakingLots <- p.id
}}
(ensemble)AvailableParkingLotsCloseToDestination
(component)ParkingLot
position
freePlaces
…
(component)ParkingLot
position
freePlaces
…
Component Vehicle = {position: IPositionavailableParkingLots: IParkingLot[]route: IRouteschedule: ISchedule…
process updatePlan {function = updatePlaninputKnowledge = [position,
availableParkingLots, …]outputKnowledge = [route, …]scheduling = periodic(1s)
…} }
Component ParkingLot = {freePlaces: Intposition: IPosition…process updateFreePlaces {
…}
}
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Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
DEECo – Architecture Abstractions
(component)ParkingLot
position
freePlaces
…
Component
Knowledge
Processes
Ensemble
Membership Condition
?Holds
Knowledge Exchange
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Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
DEECo – Architecture Abstractions(ensemble)
AvailableParkingLotsCloseToDestination Ensemble AvailableParkingLotsCloseToDestination {v: IVehiclep: IParkingLot
membership : proximity(p.position, v.route) <= DIST_THR
&& p.freePlaces >= FREE_PLACES_THR
knowledge exchange {v.availablePakingLots <- p.id
}}
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Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
DEECo – Architecture Abstractions
(ensemble)AvailableParkingLotsCloseToDestination
(ensemble)AvailableParkingLotsCloseToDestination
(ensemble)VehiclesCloseByWithTrafficUpdate
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Ensemble VehiclesCloseByWithTrafficUpdate {v1: IVehiclev2: IVehicle
membership : proximity(v1.position, v2.position) <= DIST_THR
knowledge exchange {v1.trafficInfo <- v2.trafficInfo
}}
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Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
DEECo – Architecture Abstractions
(ensemble)AvailableParkingLotsCloseToDestination
(ensemble)AvailableParkingLotsCloseToDestination
(ensemble)VehiclesCloseByWithTrafficUpdate
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Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
DEECo – Architecture Abstractions
(ensemble)AvailableParkingLotsCloseToDestination
(ensemble)AvailableParkingLotsCloseToDestination(ensemble)
VehiclesCloseByWithTrafficUpdate
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Requirements Abstractions
16Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
Invariants capture operational normalcy at every time instant
Decomposition of invariants forms design trees• Akin to goal-oriented requirements elaboration
Leaf invariants are operationalized via • Component processes and knowledge exchange functions• Monitors
Alternative decompositions provide alternative system realizations• Used at runtime to drive architecture reconfiguration
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Support for Goal-Oriented Design
17Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
GMF-based designer
Structural checking
Code generation (jDEECo)
EMF model used for runtime requirements reflection
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Support for Network Simulations
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Detailed network simulator
Rich library of communication models
Rich library of hardware models
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Support for Environment Simulations
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Agent-Based Traffic Simulator
Simulates people mobility according to their plans
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Support for Visualization
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Customizable map-based visualizationInspection of ensemble forming/disbanding
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Conclusions
21Ilias Gerostathopoulos, SEAMS ‘15, 18.05.2015 An Architecture Framework for Experimentations with Self-Adaptive Cyber-Physical Systems
Self-adaptation is hard to achieve in smart CPS
Framework for Experimentations with self-adaptive CPS
https://github.com/d3scomp/JDEECo