1. Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics Robert Schaefer, AGH University of Science and Technology, Kraków, Poland The Group Members: Maciej Smołka Jagiellonian University, Kraków, Poland Piotr Uhruski, Marek Grochowski AGH University of Science and Technology, Kraków, Poland

2. Motivation Distributed computation paradigms Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics  message passing libraries PVM Parallel Virtual Machine (1990), MPI Message-Passing Interface (1992)  SOA (Service Oriented Architecture) CORBA (1996), SOAP (1998)  GRID Condor (1997), Globus (1998), OGSI/OGSA (2002) Some drawbacks :  partially manual resources allocation  time consuming deployment and maintenance of the system  usually assuming static resources

3. Motivation Computation + Agent logic Agents environment Middleware Application Network Heterogeneous Operating Systems Distributed computing using MAS technology Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics

4. Sample task implementations Smart Solid Connections Overview of the OCTOPUS architecture Middleware Application Diffusion scheduling in multiagent computing system Java CORBA Octopus... Java CORBA Octopus Java CORBA Octopus Agents (scheduling, grain control) Agent SDK Virtual Topology VCN MotivationArchitectureAlgorithmsExamplesDynamics

5. Diffusion scheduling in multiagent computing system Architecture OCTOPUS Key Tasks  Execute Agents  Distributed Communication  Environment Information  Migration  Virtual Network Topology  Virtual Computation Node (VCN)  Agent’s Construction Kit Agents environment MotivationArchitectureAlgorithmsExamplesDynamics

6. Algorithms  Analogy to molecular diffusion phenomena  Local scheduling method – every agent is autonomously searching and allocating resources at neighbouring node  We hope to obtain the asymptotically balanced load Diffusion scheduling idea Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics

7. Diffusion schduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics Diffusion scheduling – main parameters

8. Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics Diffusion scheduling algorithm

9. Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics Binding energy formulas under consideration (2) (1)

10. Algorithms  Internal job is a dynamic structure of atomic jobs  Sequential computation of contained atomic jobs  New agent creation when the number of contained jobs exceeds the capacity of the agent Controlling the computation grain – Container agent Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics

11. Algorithms „Weak” synchronization strategy – „Leo the Professional” agent (J. Momot, K. Kossacki – 2004)  Migrates through the network and gathers information about computing agents  Responsible for removing redundancy  Allows to avoid total synchronization of the local system Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics

12. Tests Speedup vs. grain in CAE computation Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics

13. Tests Overhead of the Agent Oriented technology (the case of HGS computation) Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics

14. Tests Speedup of the Diffusion Scheduling (the case of HGS computation) Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics

15. Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics Communication dependent rules „LAN” case „WAN” emulation

16. Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics Experiments in the local area network (1)(2)

17. Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics Experiments in the wide area network (2)(1)

18. Conclusions MotivationArchitectureAlgorithmsExamplesDynamics Diffusion scheduling in multiagent computing system Preliminaries

19. Conclusions MotivationArchitectureAlgorithmsExamplesDynamics Diffusion scheduling in multiagent computing system State equations

20. Conclusions MotivationArchitectureAlgorithmsExamplesDynamics Diffusion scheduling in multiagent computing system Optimal scheduling problem

21. Conclusions Diffusion scheduling is an effective tool of managing large-scale distributed systems. It is achieved by the low complexity of local scheduling rules and only local communication. It ensures proper agent location in the dynamic network environment. Introduced formal description provides the discrete equation of evolution and the characterization of admissible controls as well as the cost functional for computing MAS. The optimal scheduling problem posses the unique solution in the class of stationary strategies. Total overhead is low in comparison with the computation time (~ 5%). No significant requirements imposed over applications. Diffusion scheduling in multiagent computing system

22. Thank you for your patience! Diffusion scheduling in multiagent computing system

23. Publications