Design of embedded multiagent systems: discussion about some specificities

Design of embedded multiagent Design of embedded multiagent systems: discussion about some systems: discussion about some

specificitiesspecificities

Jean-Paul JAMONT, Michel OCCELLOUniversity of Grenoble II

LCIS Labs{jean-paul.jamont,michel.occello}@iut-valence.fr{jean-paul.jamont,michel.occello}@iut-valence.fr

VII Agent-Oriented Software Engineering VII Agent-Oriented Software Engineering Technical ForumTechnical Forum

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INTRODUCTIONINTRODUCTION

II. Lifecycle. Lifecycle

IIII. Specific activities. Specific activities

IIIIII. An original eMAS simulation tools. An original eMAS simulation tools

CONCLUSIONCONCLUSION

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Dedicated systems built to handle one or a few pre-Dedicated systems built to handle one or a few pre-established tasks established tasks in interaction within interaction with the physical world the physical world

As consumer systems their architectures often supply As consumer systems their architectures often supply inexpensive microprocessorsinexpensive microprocessors and and limited storagelimited storage

2007: 4 440 000 000 8bit 2007: 4 440 000 000 8bit cc 2010: 6 500 000 000 8bit 2010: 6 500 000 000 8bit cc

Strong constraintsStrong constraints for embedded systems: for embedded systems: application size application size interaction with the physical world interaction with the physical world response time response time power autonomypower autonomy

Introduction : Introduction : EmbeddedEmbedded Systems Systems

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Introduction : Introduction : CooperativeCooperative EmbeddedEmbedded Systems Systems

More More constraints for cooperativeconstraints for cooperative embedded embedded systems :systems :

ComplexityComplexity ConcurrencyConcurrency Integration or composition of heterogeneous systems and servicesIntegration or composition of heterogeneous systems and services Dynamic ReconfigurationDynamic Reconfiguration MobilityMobility Data and function integrityData and function integrity

Embedded software are thus Embedded software are thus not just software not just software on small computerson small computers. .

They are conceived using software They are conceived using software built into or built into or 'embedded''embedded' within a device. The software can within a device. The software can be partly be partly 'built in''built in' to the electronics. to the electronics.

Specialized hardware architectures as Specialized hardware architectures as FPGA FPGA or or SOCSOC can be used in this context. can be used in this context.

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Building an embedded MAS doen’tBuilding an embedded MAS doen’t consist simply in consist simply in translatingtranslating agent code to another plateformagent code to another plateform

Agents of an eMASAgents of an eMAS : : OwnOwn low memorylow memory ressourcesressources 16K-32K, stack of 256 bytes16K-32K, stack of 256 bytes

OwnOwn low CPU MHzlow CPU MHz 1MHz-4MHz1MHz-4MHz

Must manages theirMust manages their autonomous energyautonomous energy Sleep/wake up mode…Sleep/wake up mode…

Embedded Embedded featuresfeatures impact impact designdesign processesprocesses, , modelsmodels, , architecturesarchitectures and and implementationsimplementations of the agentsof the agents

The transposition to a local agent model/architecture The transposition to a local agent model/architecture can insert somecan insert some deviationsdeviations in thein the global behaviorglobal behavior. .

Introduction : Introduction : EmbeddedEmbedded Multiagent Systems Multiagent Systems

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Previous works on embedded multiagent Previous works on embedded multiagent systemssystems TheThe DIAMOND methodDIAMOND method [AIAI05][AIAI05] The The MWAC modelMWAC model [IAT07][IAT07] ApplicationsApplications::

Wireless measurement systems Wireless measurement systems [Measurement10],[Measurement10],

Geolocation [CSTST08]Geolocation [CSTST08] Cooperative robotics [MARS06]Cooperative robotics [MARS06] Decentralized automation systems [CICA11]Decentralized automation systems [CICA11]

Introduction : Introduction : EmbeddedEmbedded Multiagent Systems Multiagent Systems

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II. Lifecycle. Lifecycle




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LifecycleLifecycleTraditionnal approaches vs hw/sw codesign approach

• Reduced time to market• Best design space exploration• Rapid prototyping• Simplified hw/sw integration• …

71.5% of all embedded system designs were not within 30% of pre-design performance expectations.

[Embedded Computing Design, Skazinski03]

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LifecycleLifecycle

Traditional life cycle are Traditional life cycle are waterfallwaterfall like like Gaia [Woolridge 2000], Mase [Deloach 2001]Gaia [Woolridge 2000], Mase [Deloach 2001]

MAS : few works on the MAS : few works on the deployment phasedeployment phase PASSI [Chella 2004], MASSIVE [Lind 2001]PASSI [Chella 2004], MASSIVE [Lind 2001]

Necessity of an Necessity of an iterative iterative andand incremental incremental approachapproach

[Cernuzzi 2005], Agile-PASSI [Chella 2006] [Cernuzzi 2005], Agile-PASSI [Chella 2006]

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The DIAMOND Life CycleThe DIAMOND Life Cycle

defines what the user needs and characterizes the global defines what the user needs and characterizes the global functionalitiesfunctionalities

decomposing a problem in a multiagent solution

to build the multiagent system without distinguisting hardware/software parts

partitioning the system in a hardware part and a software part partitioning the system in a hardware part and a software part to produce the code and the hardware synthesisto produce the code and the hardware synthesis

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II. . LifecycleLifecycle

IIII. . Specific activitiesSpecific activities



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Specific activitiesSpecific activitiesIn early requirementsIn early requirements

Designing embedded multi-agent systems implies Designing embedded multi-agent systems implies to treat of to treat of extra-functional requirementsextra-functional requirements related related to to deploymentdeployment. .

Most multiagent methodologies Most multiagent methodologies focus only on focus only on functional requirementsfunctional requirements whereas designing whereas designing embedded multi-agent systems imposes to treat embedded multi-agent systems imposes to treat of extra-functional requirements. of extra-functional requirements.

Some of the multiagent leader methodologies Some of the multiagent leader methodologies attempts to attempts to integrate some techniques to catch integrate some techniques to catch extra-funtional requirementsextra-funtional requirements in their last in their last extensions extensions O-Mase [Harmon09], RE-Gaia [Blanes09] .O-Mase [Harmon09], RE-Gaia [Blanes09] .

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Specific activitiesSpecific activitiesIn early requirementsIn early requirements

Another aspect to study, related to the physical context, Another aspect to study, related to the physical context, are the are the requirements in terms of safetyrequirements in terms of safety (physical risk (physical risk assessment):assessment):

the guarantee that the system will not be dangerous for the human user even in the guarantee that the system will not be dangerous for the human user even in degraded running modedegraded running mode..

Requirements expression from manufacturing systems :Requirements expression from manufacturing systems : FMEA : FMEA : Failure modes and effects analysisFailure modes and effects analysis

a qualitative hazard identification that helps to identify potential failure modes based a qualitative hazard identification that helps to identify potential failure modes based on past experience with other systems. The objective is to study the effects of those on past experience with other systems. The objective is to study the effects of those failures and how they can affect the user.failures and how they can affect the user.

[Ebrahimipour10] proposed an agent structure and used it in a multiagent system to [Ebrahimipour10] proposed an agent structure and used it in a multiagent system to ensure safety engineering by the means of faulty diagnosis diagram trying to solve ensure safety engineering by the means of faulty diagnosis diagram trying to solve limitation of FMEA in complex systems or with a process with numerous components. limitation of FMEA in complex systems or with a process with numerous components.

HAZOP : HAZOP : Hazard an Operability StudiesHazard an Operability Studies The HAZOP approach is a systematic procedure for determining the causes of process The HAZOP approach is a systematic procedure for determining the causes of process

deviations from normal behavior and consequences of those deviations.deviations from normal behavior and consequences of those deviations. [Sterling09] presents safety as a quality attribute for a multiagent system.[Sterling09] presents safety as a quality attribute for a multiagent system. A few industrial applications using multiagent have involved some HAZOP rules.A few industrial applications using multiagent have involved some HAZOP rules.

DIAMOND introduces DIAMOND introduces GEMMAGEMMA

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Study of running/stop modesSpecific activitiesSpecific activities

EMERGENCY MODE

RUNNING MODESTOP MODE & RESTART MODE

MAS IN AUTONOMOUS RUNNING

MAS IN NORMAL RUNNING

MAS STILL AUTONOMOUS

RUNNING

NORMAL STOP STATE

PROCEDURES

NORMAL STOP IN A SPECIFIED

STATE PROCEDURE

VE

RIF

ICA

TIO

N

PR

OC

ED

UR

EE

ME

RG

EN

CY

TE

ST

P

RO

CE

DU

RE

STOP PROCEDURE TO ENSURE SECURITY

DIAGNOSIS OR FAILURE

TREATMENT

PREPARATION FOR RESTART AFTER

DYSFUNCTIONNING

GOING IN A SPECIFIED

STATE

PROCEDURE TO RETURN IN INTIAL

STATE

STOP IN INITIAL STATE

ST

AR

T

PR

OC

ED

UR

ES

MAS COMPONENT VERIFICATION

IN ORDER

STOP OBTAINED

TE

RM

INA

TIO

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PR

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ES

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Specific activitiesSpecific activities In the multiagent analysisIn the multiagent analysis

Specific properties must be taken into account in multiagent Specific properties must be taken into account in multiagent models :models : IntegrationIntegration

Real world physical interactionReal world physical interaction SafetySafety

Risk Modelling Framework Risk Modelling Framework IntegrityIntegrity

Trust and ReputationTrust and Reputation MobilityMobility

Connexion maintainingConnexion maintaining TimelinessTimeliness

Real-Time CapabilitiesReal-Time Capabilities Power Management Power Management

DecisionDecision InteractionInteraction

Heterogeneity Heterogeneity Data Data InteractionInteraction

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AIM: decomposing a problem into a multiagent solution

Specific activitiesSpecific activitiesIn the multiagent analysisIn the multiagent analysis

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Specific activitiesSpecific activitiesIndividual stepIndividual step

A model for real world physical interaction integrationA model for real world physical interaction integration

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Identifying and analyzing the possible influences upon the two previous steps. Those influences are integrated within the agents by means of their communication and perception assessment capabilities.

Specific activitiesSpecific activitiesSocialization of the agentsSocialization of the agents

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Values Values observed for observed for

world world representation representation (a given state (a given state

ofofthe world)the world)

parameters of parameters of decision decision functionsfunctions

ordersordersof priority of of priority of the decision the decision (immediately (immediately

with with preemption,preemption,

after the after the current task, current task,

etc...)etc...)

receivedreceivedmessages and messages and

contents…contents…

actions (or actions (or action action

sequences)sequences)able to be able to be

triggered after triggered after the validation the validation of evaluationof evaluation

conditionsconditions

decides of the decides of the pertinence, of pertinence, of plans (actions)plans (actions)to trigger and to trigger and

of the of the emergency of emergency of

activationactivationfunction of the function of the

state of the state of the worldworld

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Reducing the gap between analysis and implementation Building flexible reconfigurable hw/sw framework [Naji04]

Mixing software agents and hardware agents [Meng05] Building agents using different embedded techniques :

System-on-Chip [Naji06] Control Theory (PID) [Breemen00] Labview [Polakow09]

Building agent using generic hw/sw components

Specific activitiesSpecific activitiesGeneric designGeneric design

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AIM: Building the multiagent system, once one knows what agents have to do without making any difference between hardware/software parts

• Building agents using components.


• Choosing technological solutions,

Received message

Flight time

Battery level

Message to deliver

Location request

<location,confidence>

Bit field (sender id 8b, receiver id 8b, data length 8b, data 0-2048b)

Bit field (sender id 1b, receiver id 1b, data length 1b, data 0-2048b)

Falling edge

Number of quantum – unsigned integer, 24b

Percentage of available energy - IEEE 754, 32b

Confidence : IEEE 754, 32b

X,Y : uint 16b, uint 16b - Shared orthonormal basis

Union – 64bits

INFORMATION SPECIFICATION

High level = 5V Low level = 0V

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AIM: partitioning the system into a hardware part and a software part to produce the code and the hardware synthesis

Criteria: cost, performance, flexibility, fault-tolerance, ergonomic constraints and the algorithmic complexity.

Specific activitiesSpecific activitiesImplementationImplementation

Criteria: cost, performance, flexibility, fault-tolerance, non-functional constraints (thermal dissipation, dimension, energy consumption …) and the algorithmic complexity.

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Specific activitiesSpecific activitiesImplementationImplementation

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II. . LifecycleLifecycle


IIIIII. . An eMAS simulation toolsAn eMAS simulation tools


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1: enables hw/sw agents society simulation

AIMSOur Hw/Sw simulatorOur Hw/Sw simulator

2: involves realistic models of : - the physical environment - the battery consumption - the wave propagation

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Work of Danny Weyns, Kurt Schelfthout, Tom Holvoet, Tom Lefever [AAMAS2005]

=> Make a virtual environment from the physical observations to plan actions

• Work of Fawzi Hassaïne, Russ Moulton, Chris Fink [SAC2009] => Have more realistic simulations

Related works

Traditional ways to design Traditional ways to design eMASeMAS

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Overview of MASHOur Hw/Sw simulatorOur Hw/Sw simulator

Demonstrated in IEEE/WIC/ACM IAT 2009 & JFSMA 2009

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Advantages of MASH Pure software simulation + enables to measure easily a lot of criteria+ allows to simplify complex decisional tasks design- The quality of the simulation depends on the quality of the different models - We have a lot amount of memory and CPU with high performance

The possibles simulations

Our Hw/Sw simulation based Our Hw/Sw simulation based approachapproach

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The possibles simulations

Our Hw/Sw simulation based Our Hw/Sw simulation based approachapproach

Advantages of MASH Hybrid software/hardware simulation + Allows to test embedded agents in a very large system (with a low cost)+ Provides a support during the debugging phase - Supplies Time management

Advantages of MASH Pure hardware simulation + The code is running on the real platform but these agents interact together through the simulated world + It is possible to debug the embedded agent with a serial debugging backchannel.+ The simulator can be used as a visualization and analysis tools+ Like in pure or hybrid software simulation, it is possible to play some scenarios- To have realistic simulations, one needs many devices and the associated financial cost is very important.

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•The DIAMOND method :

• based on a spiral lifecycle, • unifies the design of each agent as an hw/sw entity,• introduces embedded dependent specific activities.

•Using the different simulations, MASH allows to :•Design a virtual multiagent system•Prepare for the code embedding of this system,•Test the embedded multiagent system and debugger,•Evaluate the performances of this system.

A complete embedded multiagent systems design approach

ConclusionConclusion

Documents

Design of embedded multiagent systems: discussion about some specificities