Design of embedded multiagent systems: discussion about some specificities

1. VII Agent-Oriented Software Engineering  Technical Forum Design of embedded multiagent systems: discussion about some specificities Jean-Paul JAMONT, Michel OCCELLO University of Grenoble II LCIS Labs {jean-paul.jamont,michel.occello}@iut-valence.fr

2. PLAN INTRODUCTION I. Lifecycle II. Specific activities III. An original eMAS simulation tools CONCLUSION

3. Introduction : Embedded Systems • Dedicated systems built to handle one or a few pre-established tasks in interaction with the physical world • As consumer systems their architectures often supply inexpensive microprocessors and limited storage 2007: 4 440 000 000 8bit c 2010: 6 500 000 000 8bit c • Strong constraints for embedded systems: • application size • interaction with the physical world • response time • power autonomy

4. Introduction : CooperativeEmbedded Systems • More constraints for cooperative embedded systems : • Complexity • Concurrency • Integration or composition of heterogeneous systems and services • Dynamic Reconfiguration • Mobility • Data and function integrity • Embedded software are thus not just software on small computers. • They are conceived using software built into or 'embedded' within a device. The software can be partly 'built in' to the electronics. • Specialized hardware architectures as FPGA or SOC can be used in this context.

5. Introduction : Embedded Multiagent Systems • Building an embedded MAS doen’tconsist simply in translatingagent code to another plateform • Agents of an eMAS : • Ownlow memoryressources16K-32K, stack of 256 bytes • Ownlow CPU MHz1MHz-4MHz • Must manages theirautonomous energySleep/wake up mode… • Embedded features impactdesignprocesses, models, architectures and implementationsof the agents • The transposition to a local agent model/architecture can insert somedeviationsin theglobal behavior.

6. Introduction : Embedded Multiagent Systems • Previous works on embedded multiagent systems • TheDIAMOND method[AIAI05] • The MWAC model[IAT07] • Applications: • Wireless measurement systems [Measurement10], • Geolocation [CSTST08] • Cooperative robotics [MARS06] • Decentralized automation systems [CICA11]

7. PLAN INTRODUCTION I. Lifecycle II. Specific activities III. An original eMAS simulation tools CONCLUSION

8. Lifecycle • Reduced time to market • Best design space exploration • Rapid prototyping • Simplified hw/sw integration • … Traditionnal approaches vs hw/sw codesign approach 71.5% of all embedded system designs were not within 30% of pre-design performance expectations. [Embedded Computing Design, Skazinski03]

9. Lifecycle • Traditional life cycle are waterfall like • Gaia [Woolridge 2000], Mase [Deloach 2001] • MAS : few works on the deployment phase • PASSI [Chella 2004], MASSIVE [Lind 2001] • Necessity of an iterative and incremental approach • [Cernuzzi 2005], Agile-PASSI [Chella 2006]

10. The DIAMOND Life Cycle partitioning the system in a hardware part and a software part to produce the code and the hardware synthesis defines what the user needs and characterizes the global functionalities decomposing a problem in a multiagent solution to build the multiagent system without distinguisting hardware/software parts

11. PLAN INTRODUCTION I. Lifecycle II. Specific activities III. An original eMAS simulation tools CONCLUSION

12. Specific activitiesIn early requirements • Designing embedded multi-agent systems implies to treat of extra-functional requirements related to deployment. • Most multiagent methodologies focus only on functional requirements whereas designing embedded multi-agent systems imposes to treat of extra-functional requirements. • Some of the multiagent leader methodologies attempts to integrate some techniques to catch extra-funtional requirements in their last extensions • O-Mase [Harmon09], RE-Gaia [Blanes09] .

13. Specific activitiesIn early requirements • Another aspect to study, related to the physical context, are the requirements in terms of safety (physical risk assessment): • the guarantee that the system will not be dangerous for the human user even in degraded running mode. • Requirements expression from manufacturing systems : • FMEA : Failure modes and effects analysis • 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 failures and how they can affect the user. • [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 limitation of FMEA in complex systems or with a process with numerous components. • HAZOP : Hazard an Operability Studies • The HAZOP approach is a systematic procedure for determining the causes of process deviations from normal behavior and consequences of those deviations. • [Sterling09] presents safety as a quality attribute for a multiagent system. • A few industrial applications using multiagent have involved some HAZOP rules. • DIAMOND introduces GEMMA

14. Specific activities Study of running/stop modes

15. Specific activitiesIn the multiagent analysis • Specific properties must be taken into account in multiagent models : • Integration • Real world physical interaction • Safety • Risk Modelling Framework • Integrity • Trust and Reputation • Mobility • Connexion maintaining • Timeliness • Real-Time Capabilities • Power Management • Decision • Interaction • Heterogeneity • Data • Interaction

16. Specific activities In the multiagent analysis AIM: decomposing a problem into a multiagent solution

17. Specific activities Individual step A model for real world physical interaction integration

18. Specific activities Socialization of the agents 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.

19. orders of priority of the decision (immediately with preemption, after the current task, etc...) Values observed for world representation (a given state of the world) received messages and contents… parameters of decision functions actions (or action sequences) able to be triggered after the validation of evaluation conditions decides of the pertinence, of plans (actions) to trigger and of the emergency of activation function of the state of the world

20. Specific activities Generic design • 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

21. Specific activities Generic design AIM: Building the multiagent system, once one knows what agents have to do without making any difference between hardware/software parts • Choosing technological solutions, • Building agents using components.

22. Specific activities Generic design

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

24. Specific activities Implementation

26. PLAN INTRODUCTION I. Lifecycle II. Specific activities III. An eMAS simulation tools CONCLUSION

27. Our Hw/Sw simulator 1: enables hw/sw agents society simulation AIMS 2: involves realistic models of : - the physical environment - the battery consumption - the wave propagation

28. Traditional ways to design eMAS Related works • 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

29. Our Hw/Sw simulator Overview of MASH Demonstrated in IEEE/WIC/ACM IAT 2009 & JFSMA 2009

30. Our Hw/Sw simulation based approach The possibles simulations Advantages of MASHPure software simulation • + enables tomeasure easilya lot of criteria • + allows tosimplify complex decisionaltasks design • The quality of the simulation depends on thequality of the different models • We have alot amount of memoryand CPU with high performance

31. Our Hw/Sw simulation based approach The possibles simulations Advantages of MASH Hybrid software/hardware simulation + Allows totest embedded agents in a very largesystem (with a low cost) + Provides asupport during the debugging phase - Supplies Time management Advantages of MASHPure hardware simulation + Thecode is running on the real platformbut these agentsinteract together through the simulated world + It is possible todebug the embedded agentwith a serial debugging backchannel. + The simulator can be used as avisualization and analysis tools + Like in pure or hybrid software simulation, it is possible toplay some scenarios - To have realistic simulations, one needs many devices and the associatedfinancial cost is very important.

32. Conclusion • 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 : • Designa virtual multiagent system • Prepare for the codeembedding of this system, • Test the embedded multiagentsystem and debugger, • Evaluate theperformancesof this system. •  A complete embedded multiagent systems design approach