Probabilistic Analysis of a Network Resource Allocation Algorithm.

Abstract

A distributed algorithm is presented, for allocating a large number of identical resources (such as airline tickets) to requests which can arrive anywhere in a distributed network. Resources, once allocated, are never returned. The algorithm searches sequentially, exhausting certain neighborhoods of the request origin before proceeding to search at greater distances. Choice of search direction is made nondeterministically. Analysis of expected response time is simplified by assuming that the search direction is chosen probabilistically, that messages require constant time, that the network is a tree with all leaves at the same distance from the root, and that requests and resources occur only at leaves. It is shown that the response time is approximated by the number of messages of one that are sent during the execution of the algorithm, and that this number of message is a nondecreasing function of the interarrival time for requests. Therefore, the worst case occurs when requests come in so far apart that they are processed sequentially. The expected time for the sequential case of the algorithm is analyzed by standard techniques. This time is shown to be bounded by a constant, independent of the size of the network. It follows that the expected response time for the algorithm is bounded in the same way. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1985
Accession Number
ADA157553

Entities

People

  • Leonidas J. Guibas
  • M. J. Fischer
  • N. A. Lynch
  • N. Griffeth

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computer Science
  • Computers
  • Equations
  • Inequalities
  • Information Processing
  • Information Science
  • Information Systems
  • Massachusetts
  • Military Research
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Sequences
  • Sequential Analysis
  • Standards
  • Trees (Data Structures)

Fields of Study

  • Computer science

Readers

  • Mathematical Modeling and Probability Theory.
  • Operations Research
  • Public Financial Management and Budgeting