Conference Paper

Optimal DiffServ AC Design using Non-Linear Programming.

PUCPR, Brazil
DOI: 10.1109/LCN.2007.32 Conference: 32nd Annual IEEE Conference on Local Computer Networks (LCN 2007), 15-18 October 2007, Clontarf Castle, Dublin, Ireland, Proceedings
Source: DBLP

ABSTRACT Most DiffServ admission control (AC) algorithms rely on tuning parameters to help in the decision making. Tuning these parameters is a difficult task, especially when one considers the problem of assuring QoS guarantees to individual flows. This paper proposes a method for helping the design of DiffServ AC algorithms based on non-linear programming optimization. It enables to find the values for the AC parameters that permits to satisfy the QoS guarantees for individual VoIP flows, while minimizing a cost function that represents the performance goals of the service provider. This approach is used to compare the performance of some commonly used DiffServ AC techniques and also to design a novel AC algorithm based on queue estimates.

0 Followers
 · 
74 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The Nelder{Mead simplex algorithm, rst published in 1965, is an enormously pop- ular direct search method,for multidimensional unconstrained minimization. Despite its widespread use, essentially no theoretical results have been proved explicitly for the Nelder{Mead algorithm. This paper presents convergence properties of the Nelder{Mead algorithm applied to strictly convex functions in dimensions 1 and 2. We prove convergence to a minimizer for dimension 1, and various limited convergence results for dimension 2. A counterexample of McKinnon gives a family of strictly convex functions in two dimensions and a set of initial conditions for which the Nelder{Mead algo- rithm converges to a nonminimizer. It is not yet known,whether the Nelder{Mead method,can be proved to converge to a minimizer for a more specialized class of convex functions in two dimensions. Key words. direct search methods, Nelder{Mead simplex methods, nonderivative optimization AMS subject classications. 49D30, 65K05 PII. S1052623496303470
    SIAM Journal on Optimization 01/1998; 9(1-1):112-147. DOI:10.1137/S1052623496303470 · 2.11 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper explores the differences that can exist between individual and aggregate loss guarantees in an environment where guarantees are only provided at the aggregate level. The focus is on understanding which traffic parameters are responsible for inducing possible deviations and to what extent. In addition, we seek to evaluate the level of additional resources, e.g., bandwidth or buffer, required to ensure that all individual loss measures remain below their desired target. This paper's contributions are in developing analytical models that enable the evaluation of individual loss probabilities in settings where only aggregate losses are controlled, and in identifying traffic parameters that have a major influence on the differences between individual and aggregate losses. The latter allows us to further construct practical tools and guidelines for rapidly assessing if specific traffic sources can be safely multiplexed into a common service class.
    01/2002
  • [Show abstract] [Hide abstract]
    ABSTRACT: The transition from sequential to parallel computation is an area of critical concern in today's computer technology, particularly in architecture, programming languages, systems, and artificial intelligence. This book addresses issues in concurrency, and by producing both a syntactic definition and a denotational model of Hewitt's actor paradigm - a model of computation specifically aimed at constructing and analyzing distributed large-scale parallel systems - it advances the understanding of parallel computation.
    01/1990; MIT Press., ISBN: 978-0-262-01092-4