Buffering and Flow Control in Message Switched Communication Networks

Abstract

The mathematical study of buffering and flow control is based on a gradual input queueing model. The gradual input model has been used previously to study data multiplexors. Here it is extended to an entire message switched communication network. A probability of buffer overflow analysis is developed and used to determine buffer requirements. A delay analysis is also developed. The results obtained using the gradual input queue are compared to the commonly used M/M/1 queue model for message switched networks. The gradual input model allows one to observe several effects due to a finite number of finite rate traffic sources in such networks that cannot be observed using the M/M/1 model. Flow control is studied in tree concentration structures. The flow control assures that buffer overflows will occur only at source nodes, not in the interior of the tree. The problem of finding the buffer allocation that minimizes the probability of buffer overflow in such a tree is studied. It is shown that in certain cases it is optimal to place all buffers at source nodes. This is, however, not always so and insight into this is given by example. Determining the performance of a tree structure in which flow control is being used is a difficult analytic problem. An approximate analysis based on a first passage time theorem for Markov chains is therefore developed for an example. The approximate analysis is verified by simulation.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1978
Accession Number
ADA051165

Entities

People

  • Eberhard F. Wunderlich

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Channel Capacity
  • Communication Channels
  • Communication Networks
  • Communication Systems
  • Computer Communications
  • Computer Networks
  • Computers
  • Digital Communications
  • Electrical Engineering
  • Markov Chains
  • Markov Processes
  • Networks
  • Probability
  • Random Variables
  • Simulations
  • Stochastic Processes
  • Throughput

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Computer Networking