1 / 13

IOA: Distributed Algorithms  Distributed Programs

I. A. O. IOA: Distributed Algorithms  Distributed Programs. Nancy Lynch PODC 2000 Collaborators: Steve Garland, Josh Tauber, Anna Chefter, Antonio Ramirez, Michael Tsai, Mandana Vaziri, Tina Nolte. What we want to do:.

makela
Download Presentation

IOA: Distributed Algorithms  Distributed Programs

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. I A O IOA: Distributed Algorithms  Distributed Programs Nancy Lynch PODC 2000 Collaborators: Steve Garland, Josh Tauber, Anna Chefter, Antonio Ramirez, Michael Tsai, Mandana Vaziri, Tina Nolte

  2. What we want to do: See how abstract I/O automatonmodels of distributed algorithms and services could be used in producing and maintaining actual distributed programs.

  3. Why use models in programming? • Models let you: • Build complex things and get them right • Change things and understand the consequences • Explain clearly how things work • Other engineering disciplines use them

  4. But why I/O automaton models? • Simple mathematical basis for describing structure + behavior of systems of interacting components • Already used for: • Distributed algorithms, impossibility results • System case studies: • Group communication services (Orca, Transis, Ensemble,…) • Communication protocols (TCP, T/TCP,…) • Hybrid (continuous/discrete) systems (TCAS,…)

  5. I/O automata[Lynch, Tuttle 87] • Nondeterministic state machines • Infinite state • Input/output/internal actions • Transitions, executions, traces • Supports modularity: • Composition • Levels of abstraction • Mathematical model, language-independent

  6. How I/O automata are used • Model service specs, distributed algorithms • Refine, from high level global service spec to detailed distributed algorithm: • Make models as nondeterministic as possible • Prove correctness, using invariants, simulation relations, composition

  7. TO TO Broadcast Service Spec [Fekete, Lynch, Shvartsman, PODC 97] Signature: input: broadcast(a,p) output: receive(a,p,q) internal: order(a,p) State: queue, sequence of (a,p), initially empty for each p: pending[p], sequence of a, initially empty next[p], positive integer, initially 1

  8. Transitions: broadcast(a,p) Effect: append a to pending[p] order(a,p) Precondition: a is head of pending[p] Effect: remove head of pending[p]; append (a,p) to queue receive(a,p,q) Precondition: queue[next[q]] = (a,p) Effect: next[q] := next[q] + 1 TO Broadcast

  9. I A O For proofs For simulation, code generation IOA Language[Garland, Lynch 97] • Programming/specification language for defining I/O automata • Similar to pseudocode • Explicitly describes: • Signature, structured state, precondition/effects • Nondeterministic choice, composition, invariants, levels of abstraction • Declarative + imperative

  10. IOA Tools • Front end: Parser, static checker, intermediate Java representation [Garland, Ramirez] • Support for: • Composing models [Chefter 98] [Garland, Lynch] • Refining models, from global specification to low-level distributed algorithm model: Step correspondence [Ramirez 00]

  11. IOA Tools • Prototype code generator, for generating distributed code from low-level distributed algorithm models [Tauber, Tsai] • Validation tools: • Simulator [Chefter 98] [Ramirez 00] Paired simulation: • Theorem-prover interfaces: PVS [Devillers], Isabelle? LP? NuPRL? [Nolte] • Automatic?

  12. Modeling Projects • Distributed spanning tree algorithms [Luhrs, Nolte] • Distributed replicated data management algorithms: Lamport state machines; Attiya, Bar-Noy, Dolev, … [Dean, Karlovich, Rosen] • Future: • Practical communication protocols, services • Interacting Java objects

  13. TLA and IOA • TLA and IOA both: • Use precondition/effect style • Support nondeterministic choice • Support similar kinds of assertional proofs • TLA: • Is typeless • Is declarative • Has good automatic tools • IOA: • Uses Larch Shared Language data types • Declarative + imperative • Emphasizes system decomposition

More Related