Designing Broadcast Schedules for Information Dissemination through Braodcasting

Abstract

Broadcast data delivery is encountered in many applications where there is a need to disseminate information to a large user community in a wireless asymmetric communication environment. In this paper, the authors consider the problem of scheduling the data broadcast such that the average response time experienced by users is low. In a push-based system, where the users cannot place requests directly to the server and the broadcast schedule should be determined based solely on access probabilities, they formulate a deterministic dynamic optimization problem, the solution of which provides the optimal broadcast schedule. Properties of the optimal solution are obtained and then they propose a suboptimal dynamic policy that achieves average response time close to the lower bound. The policy has low complexity, is adaptive to changing access statistics, and is easily generalizable to multiple broadcast channels. In a pull-based system where the users may place requests about information items directly to the server, the scheduling can be based on the number of pending requests for each item. Suboptimal policies with good performance are obtained in this case as well. Finally, it is demonstrated by a numerical study that as the request generation rate increases, the achievable performance of the pull- and push-based systems becomes almost identical.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1997
Accession Number
ADA439454

Entities

People

  • Chi-jiun Su
  • Leandros Tassiulas
  • Vassilis Tsotras

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Communication Channels
  • Communication Networks
  • Computational Complexity
  • Computer Programming
  • Computer Science
  • Demographic Cohorts
  • Department Of Defense
  • Dynamic Programming
  • Electrical Engineering
  • Engineering
  • Information Systems
  • Probability
  • Scheduling (Production)
  • Simulations
  • Stationary Processes
  • Universities

Fields of Study

  • Computer science
  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Networking
  • Geospatial Intelligence and Artificial Intelligence Analytics