Applications of the Theory of Distributed and Real Time Systems to the Development of Large-Scale Timing Based Systems.

Abstract

This report summarizes the progress of research in the theory of distributed systems group. Members of the group have been active during this period in modeling, designing, and developing applications for concurrent systems. Our main theme is to support highly effective concurrent application designs by providing specification, quantification, and verification tools that capture behavior without limiting performance. We have developed a new 'hybrid automata model' for analyzing the behaviors of systems like industrial robots or computer controlled Vehicles. We have made progress in applying our specification and automated verification methods to several complicated test problems in distributed computing. We have introduced a variety of new approaches to evaluating concurrent algorithms, among them 'eventual serializability,' 'linearizability,' and a novel local measure of linearizability for load balancing data structures. We are using our methods for specifying (and helping in redesigning) and a variety of new and old communication and coordination algorithms, among them Lamport's Paxos algorithm, TCP and T-TCP, and Randomized Agreement. Finally, we have shown the effectiveness of our methods in the emerging area of specifying and designing automated transit systems.

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Document Details

Document Type
Technical Report
Publication Date
Jan 26, 1996
Accession Number
ADA303752

Entities

People

  • Nancy Lynch

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Automata
  • Case Studies
  • Computer Science
  • Computers
  • Consensus Algorithms
  • Digital Television
  • Distributed Computing
  • Electrical Engineering
  • Hybrid Systems
  • Language
  • Massachusetts
  • Mathematical Models
  • Models
  • Simulations
  • Students

Fields of Study

  • Computer science

Readers

  • Mathematical Modeling and Probability Theory.
  • Parallel and Distributed Computing.
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Autonomy - Autonomous System Control