A New Paradigm for On-Line Management of Communication Networks with Multiplicative Feedback Control

Haining Yu and Christos G. Cassandras

Chapter Chapter 12 in Performance Evaluation and Planning Methods for the Next Generation Internet, 2005, pp 297-332 from Springer

Abstract: Abstract We describe the use of Stochastic Flow Models (SFMs) for control and optimization (rather than performance analysis) of computer networks. After reviewing earlier work applying Infinitesimal Perturbation Analysis (IPA) to SFMs without feedback or with additive feedback, we consider systems operating with a multiplicative feedback control mechanism. Using IPA, we derive gradient estimators for loss and throughput related performance metrics with respect to a feedback gain parameter and show their unbiasedness. We also illustrate the use of these estimators in network control by combining them with standard gradient-based stochastic approximation schemes and providing several simulation-based examples.

Keywords: Sample Path; Inflow Rate; Discrete Event System; Random Early Detection; Buffer Content (search for similar items in EconPapers)
Date: 2005
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-0-387-25551-4_12

Ordering information: This item can be ordered from
http://www.springer.com/9780387255514

DOI: 10.1007/0-387-25551-6_12

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().