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

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

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

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

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

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

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

Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics Diffusion scheduling algorithm

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

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

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

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

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

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

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

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

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

Conclusions MotivationArchitectureAlgorithmsExamplesDynamics Diffusion scheduling in multiagent computing system Preliminaries

Conclusions MotivationArchitectureAlgorithmsExamplesDynamics Diffusion scheduling in multiagent computing system State equations

Conclusions MotivationArchitectureAlgorithmsExamplesDynamics Diffusion scheduling in multiagent computing system Optimal scheduling problem

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

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