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Loss ratio approximations in buffered systems with regulated inputs

Published: 11 October 2006 Publication History

Abstract

The estimation of the expected traffic loss ratio (workload loss ratio, WLR) is a key issue in provisioning Quality of Service in packet based communication networks. The stationary (long run) loss ratio in queuing analysis is usually estimated through other assessable quantities, typically based on the approximates of the buffer overflow probability. These approaches have the drawback, that the relation between loss ratio and buffer overflow probability is often hardly quantifiable and it can in principle be arbitrary. In this paper we present novel upper approximations for workload loss ratio derived from the original definition of stationary loss ratio. These direct bounds are applicable for general service curve network elements with regulated flows acting as inputs. The performance of these bounds is systematically analyzed and compared to prior indirect (based on buffer saturation probability) loss ratio bound and its newly developed improvements. The extensive numerical investigations also exemplify that in most cases our novel direct bounds can lead to significant save in buffer requirements when guaranteeing a prescribed QoS level in terms of loss ratio.

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Cited By

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  • (2019)Network queue and loss analysis using histogram-based traffic modelsComputer Communications10.1016/j.comcom.2009.08.01133:2(190-201)Online publication date: 4-Jan-2019
  • (2013)Extending Stochastic Network Calculus to Loss AnalysisThe Scientific World Journal10.1155/2013/9185652013:1Online publication date: 20-Oct-2013
  • (2010)An Extended Stochastic Loss Bound with Moment Generating FunctionProceedings of the 2010 International Conference on Communications and Mobile Computing - Volume 0110.1109/CMC.2010.64(498-502)Online publication date: 12-Apr-2010

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cover image ACM Other conferences
valuetools '06: Proceedings of the 1st international conference on Performance evaluation methodolgies and tools
October 2006
638 pages
ISBN:1595935045
DOI:10.1145/1190095
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 October 2006

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Cited By

View all
  • (2019)Network queue and loss analysis using histogram-based traffic modelsComputer Communications10.1016/j.comcom.2009.08.01133:2(190-201)Online publication date: 4-Jan-2019
  • (2013)Extending Stochastic Network Calculus to Loss AnalysisThe Scientific World Journal10.1155/2013/9185652013:1Online publication date: 20-Oct-2013
  • (2010)An Extended Stochastic Loss Bound with Moment Generating FunctionProceedings of the 2010 International Conference on Communications and Mobile Computing - Volume 0110.1109/CMC.2010.64(498-502)Online publication date: 12-Apr-2010

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