CDC2000 Stochastic Models for Communication Networks

Stochastic Models for Communication Networks
Home Full List of Titles 1: Proceedings of CDC2000 Discrete Event Systems Control in Communication Systems Optimal Control and Applications I Optimisation Approaches and Methods Model Predictive Control Advances in Linear Estimation Stochastic and Uncertain Systems Nonlinear Control and Applications Nonlinear Estimation and Filtering Formation Control and its Applications New Approaches to Fuzzy Control Manufacturing Systems Automotive Applications Stability Issues in Hybrid Control Recent Advances in Stochastic Networks Optimal Control and Applications II Robust Controller Design - mu, L1 and H2 Constrained and Receding Horizon Control Identification and Control around the World Markov Decision Processes Nonlinear Optimisation Observers for Nonlinear Systems Motion Planning Neural / Fuzzy Stability and Control Motor Control Control of Quantum Phenomena I Hybrid Systems Methods Control in Communication Networks Robustness and Optimisation Bumpless Transfer, Antiwindup and Saturation Adaptive Control: Linear Systems Estimation and Closed Loop Identification Control of Markov Processes Nonlinear Filtering and Control Modelling, Identification and Validation of Nonlinear Systems Differential Geometric Control Theory for Mechanical Systems Nonlinear Output Feedback Control Pneumatics and Compression Systems Control of Quantum Phenomena II Stability of Hybrid Systems Performance Analysis in Communication Networks Adaptive Control of Nonlinear Systems LMI Methods in Design Robust Control of Time Delay Systems Subspace Identification Methods Nonlinear Stochastic Filtering and Estimation Bifurcations, Chaos and Control I New Progress in Synthesis of Nonlinear Systems I Implementation Issues of Sliding Mode Control Theory Control of Mixing in Shear Flows Novel Neural Network Control Techniques for Industrial Motion Control Systems Physiological Control Systems Optimal Control of Hybrid Systems Stochastic Models for Communication Networks Control and Stabilisation of Nonlinear Systems New Directions in Robust Control Linear Systems Theory Advanced Topics in Systems Theory Estimation in Action Bifurcations, Chaos and Control II New Progress in Synthesis of Nonlinear Systems II Numerical Design and Analysis Techniques for Nonlinear Systems Analysis and Control of Underactuated Systems Sliding Mode Control I Challenges in the Application of Control to Computer Systems Estimation and Diagnosis of Discrete Event Systems Communications and Games Optimal Control Stochastic Systems Model Reduction Methodologies Identification and Subspace Methods Applications of Nonlinear Adaptive Control Advances in Nonlinear Output Feedback Design The Behavioural Approach to Systems and Control Vision Based Estimation and Control: Recent Advances and Open Problems Agile Control of Military Operations Sliding Mode Control II Model-based Fault Diagnosis of Industrial Processes Discrete Event Systems / Petri Nets System Identification and Confidence Estimation New Approaches to H-Infinity Control I Probabilistic Approaches to Robust Control Time Delay System Stabilisation Identification Methods Controlled Stochastic Processes Output Feedback of Nonlinear Systems Topics in Nonlinear Stabilisation Mobile Robots: Tracking Control Robust Control of Nonlinear Systems Power Systems Stabilisation and Control Disk Drive Control Hybrid Control Applications Discrete Time Systems New Approaches to H-Infinity Control II Linear Systems with Saturating Actuators New Theories in Distributed Parameter Systems Applications of Estimation and Identification Stochastic Control and Tuning Methodologies Control of Nonlinear Systems Iterative Learning and Control Coordinating Robot Systems Nonlinear Time Varying Systems Novel Applications of Neural Networks Aerospace Applications Switched Systems Implicit and Descriptor Systems LQG Periodic Systems and Disturbances New Horizons for Distributed Parameter Systems State Estimation Learning and Neuro-Control Nonlinear Control and Stabilisation I Tracking Vision Servoing Controllability of Nonlinear Systems Control of Flexible Systems Electro-Mechanical Systems Robust Control Methods and Applications Fault Detection and Diagnosis Optimisation and Applications Robust Stability Analysis Numerical Methods in Control Filtering in Continuous Time Stochastic Systems Interplay between Control and Signal Processing Fault Detection and Analysis Nonlinear Dynamical Systems Nonlinear Time Delay Systems Computational Issues in Nonlinear Control Disturbance Rejection Process Control Industry Applications Linear Parameter Varying Systems Linear Control Systems Dynamic and Nonlinear Programming Model Reduction Applications New Techniques for Control and Systems: Numerical Linear Algebra Estimation and Identification using Hidden Markov Models Applications of Stochastic Control Topics in Linear Design Nonlinear Control and Stabilisation II Ambulatory Robot Systems Chaotic and Oscillatory Systems Biomedical System Control Integrated Control and CPU Scheduling Linear Design Techniques Adaptive Disturbance / Noise Compensation Nonlinear Model Predictive Control Sensitivity Design, Analysis and Limitations Analysis of Linear Systems Linear Matrix Inequalities in Design Lyapunov's 2nd Method Robotics: Tracking Control Lagrangian and Hamiltonian Theory Variable Structure Control Machine Vision Signal Processing Methods in Control Applied Nonlinear Control Author Index A B C D E F G H I J K L M N O P Q R S T U V W X Y Z	Optimal Admission Control for High Speed Networks: A Dynamic Programming Approach Authors: Tania Jiménez, Volume: 1, Page 1846 Paper number 1501 Abstract: We consider in this paper the problem of Call Admission Control of guaranteed performance (GP) connections (such as the CBR and VBR traffic classes in ATM) in the presence of best effort (BE) connections that use the bandwidth left over by the guaranteed performance connections. We assume that the BE sessions do not require a minimum cell rate (MCR) and are thus not subject to call admission control. By slightly increasing rejection rate of GP sessions one may decrease dramatically the delay of BE sessions. We formulate the admission problem as a Markov decision problem and obtain the optimal policy. In particular, we show that it is of a switching curve type. We then compare numerically the performance of the optimal policy to threshold policies as well as to the policy which ignores the BE traffic (and accepts GP sessions as long as there is available bandwidth for them). We show that threshold policies are good approximations for the overall optimal policy. CD001501.PDF (From Author) TOP Simplex Convexity With Application To Open Loop Stochastic Control In Networks Authors: Eitan Altman, Bruno Gaujal, Arie Hordijk, Volume: 1, Page 1852 Paper number 1502 Abstract: In this paper, we present the notion of multimodular triangulation under a new geometrical point of view. We also show the link with multimodular functions by a new proof of the convexity theorem. This is used to define a partial ordering compatible with multimodularity called the cone ordering. An application in admission control in queues is then presented. CD001502.PDF (From Author) TOP A Markov Decision Model for Intruder Location in IP Networks Authors: Timothy Darling, Mark A. Shayman, Volume: 1, Page 1858 Paper number 1503 Abstract: We consider the problem of locating an intruder in an IP domain using dynamic IPSec security associations as proposed in the DECIDUOUS project. We formulate this problem as a Markov decision process that evolves on the set of subtrees of a shortest path routing tree. For small domains, an optimal stationary policy can be determined by dynamic programming. For large domains, the use of neurodynamic programming as well as heuristic policies are examined. Our results indicate that under certain assumptions, a one-feature heuristic policy provides good performance. CD001503.PDF (From Author) TOP Fault Management in Communication Networks: Test Scheduling with a Risk-Sensitive Criterion and Precedence Constraints Authors: Mark A. Shayman, E. Fernández-Gaucherand, Volume: 1, Page 1864 Paper number 1504 Abstract: We consider the problem of determining the optimal sequence of tests for the discovery of a faulty component, e.g., in a telecommunications network, where there is a random cost associated with testing a component. A novel feature in our approach is that a risk-sensitive performance criterion is used in order to rank different competing schedules. We characterize optimal schedules both when the testing sequence is not subject to precedence constraints, and when it is subject to such constraints, given by an arbitrary partial order. CD001504.PDF (From Author) TOP Stochastic Approximation and Transaction-Level Model for IP Network Design Authors: Linhai He, Jean Walrand, Volume: 1, Page 1870 Paper number 1505 Abstract: We investigate the use of simulation and transaction-level models for TCP in IP network design. More specifically, we focus on the transaction level dynamics of TCP and approximate it by max-min fair sharing. Based on this model, we formulate a network dimensioning problem as a nonlinear constrained optimization problem. The constraints and their gradients, which do not have analytical forms, are estimated through fluid simulation of the transaction-level model of TCP. The problem is solved by a gradient descent type of algorithm, with additional heuristics based techniques to improve its convergence. The performance of the proposed algorithm is evaluated through experimental studies on example networks. Results show that the methods are promising and can help the design of networks. CD001505.PDF (From Author) TOP Refinements to CLT-Based MBAC Schemes Using Moderate Deviations Authors: Sarang Wagholikar, R. Ravikanth, R. Srikant, Volume: 1, Page 1876 Paper number 1506 Abstract: Central limit theorem (CLT) based techniques have been recently proposed to perform measurement-based admission control (MBAC). In this paper, we present refinements to this using moderate deviations expansions of the probability of overflow in a bufferless model. CD001506.PDF (From Author) TOP