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Extending stochastic network calculus to loss analysis.

Chao Luo1, Li Yu, Jun Zheng

  • 1National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China.

Thescientificworldjournal
|November 15, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a novel "loss factor" to stochastic network calculus, enabling better analysis of data loss in computer networks. This new parameter helps derive loss bounds, improving Quality of Service (QoS) guarantees.

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Area of Science:

  • Computer Science
  • Network Engineering
  • Performance Analysis

Background:

  • Quality of Service (QoS) is crucial for network performance.
  • Stochastic network calculus primarily analyzes delay and backlog, with limited focus on data loss.
  • Deterministic network calculus has explored loss analysis, but stochastic methods are underdeveloped.

Purpose of the Study:

  • To extend stochastic network calculus for analyzing data loss.
  • To introduce a new parameter, the "loss factor," for loss bound derivation.
  • To validate the method for networks with multiple input flows.

Main Methods:

  • Introducing the "loss factor" parameter into stochastic network calculus.
  • Deriving loss bounds using existing arrival and service curves with the new parameter.
  • Applying the derived method to networks with multiple input flows.
  • Conducting simulations to analyze factors influencing the loss factor.

Main Results:

  • A novel method for calculating loss bounds in stochastic network calculus was developed.
  • The derived loss bounds are applicable to networks with multiple input flows.
  • Simulations demonstrated the influence of buffer size, arrival traffic, and service on the loss factor.

Conclusions:

  • The introduced "loss factor" effectively extends stochastic network calculus for loss analysis.
  • The findings provide a valuable tool for improving QoS by managing network data loss.
  • The method is robust and applicable to complex network scenarios with multiple traffic sources.