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Towards Next Generation Panel at SAINT 2002

Towards Next Generation Panel at SAINT 2002. Gul Agha Professor of Computer Science and Computational Science and Engineering University of Illinois at Urbana-Champaign http://www.osl.cs.uiuc.edu. Research Directions. What are the programming models for Applications on the Internet?

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Towards Next Generation Panel at SAINT 2002

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  1. Towards Next GenerationPanel at SAINT 2002 Gul Agha Professor of Computer Science and Computational Science and Engineering University of Illinois at Urbana-Champaign http://www.osl.cs.uiuc.edu

  2. Research Directions • What are the programming models for Applications on the Internet? • Massively parallel, distributed and mobile. • Multi-agent Systems • Actors • Network Embedded Systems • Integration of continuous and discrete processes.

  3. Large Scale Actor Systems Reasoning about large-scale agent systems. • Asynchrony: • Autonomous agents that communicate asynchronously. • Modularity: • Concurrent components each with several agents. • Locality and Non-interference: • Message are the only means of information flow. • Mobility: • Reconfiguration and extension of systems.

  4. Formal Methods • Probabilistic reasoning about distributed and mobile real-time systems: • Techniques for analysis of algorithms. • Performance models. • Models must account for: • Stochastic duration of actions. • Probabilistic behavior of node or system. • Uncertainty in the environment.

  5. Metrics for Large-Scale Systems • Probabilities on evolution of system. • Quantifying robustness, stability, timeliness, … • Summations over execution paths for statistical metrics..

  6. Models of Time • Global synchronous wall clock • Synchronization is too tight • Too detailed an execution model • Asynchronous, distributed time • Vector clocks are too expensive • Application behavior is complicated Need a more expressive model of time: • Notion of distance and distribution. • Space-Time cone of causal influence.

  7. Causality and Time t Future causality R P Q Not Causally related x S Past causally connected y

  8. Agents with Bounded Resources • Each agent has bounded resources. • Dynamic binding of agents to computational and network resources. • Control of Multi-Agent Systems by bounding resources: • Stability • Efficiency • Optimizing search • Preventing denial of service attacks

  9. Coordination Algorithms Large-scale systems where: • Nodes and links have variable capabilities. • Real-time requirements in the absence of a predefined global clock. • Faults are common.

  10. Example: Global Snapshot • Consistent with causal relations. • Real-time constraints: • Duration of snapshot “skew”. • Completion time of snapshot. • Scalable • Minimize number of messages. • Dynamic topology of nodes and channels. • Notion of approximation in snapshots: • Farther apart nodes have larger skews.

  11. New Directions • Hybrid Systems • Network Embedded Systems • More complex middleware • Naming • Computational Reflection • World-Wide Computer • Mobility • Grid-based computing

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