Guidelines for Sizing Traffic Queues in Terminals of Future Protected SATCOM Systems

Abstract

Future Military Satellite Communication systems will feature Time-Division Multiple Access (TDMA) uplinks in which uplink resources will be granted on demand to each terminal by a centralized resource controller. Due to the time-shared nature of the uplink, a terminal will not be constantly transmitting. It will only transmit in its assigned timeslots so as not to cause interference to other terminal transmissions. Packets arriving at a terminal during idle transmission periods will have to be buffered or queued, potentially in a terminal router, else they will be dropped. At the next assigned timeslot these queues will be serviced via a queue scheduling policy that maintains Quality-of-Service (QoS) requirements to the different traffic classes. These queues must be sized large enough to ensure no packet loss when operating in an uncongested state; how large is a function of the distribution of timeslots assigned to the terminal. In this paper, we investigate the relationship between timeslot assignment distributions and queue requirements of a terminal router providing insight of how to size router queues given an assigned timeslot distribution, or reciprocally, constraints placed on timeslot distribution given a set queue size, in order to avoid packet loss.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2009
Accession Number
ADA535149

Entities

People

  • Jeffrey Wysocarski
  • Jun Sun
  • Mu-cheng Wang

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Advanced Electronics

DTIC Thesaurus Topics

  • Air Force
  • Data Rate
  • Ethernet
  • Flow
  • Generators
  • Governments
  • Hypervelocity Flow
  • Modems
  • Multiplexing
  • Network Protocols
  • Networks
  • Packet Loss
  • Scheduling (Production)
  • Terminals
  • Time Intervals
  • United States
  • United States Government

Fields of Study

  • Computer science

Readers

  • Mathematical Modeling and Probability Theory.
  • Mycotoxin ecology in Amazonian ecosystems.
  • Radio communications and signal processing.

Technology Areas

  • Space