Convergent activation dynamics in continuous time networks
Neural Networks
Random early detection gateways for congestion avoidance
IEEE/ACM Transactions on Networking (TON)
A one-measurement form of simultaneous perturbation stochastic approximation
Automatica (Journal of IFAC)
Some Pathological Traps for Stochastic Approximation
SIAM Journal on Control and Optimization
The O.D. E. Method for Convergence of Stochastic Approximation and Reinforcement Learning
SIAM Journal on Control and Optimization
Utility-based rate control in the Internet for elastic traffic
IEEE/ACM Transactions on Networking (TON)
ACM Transactions on Modeling and Computer Simulation (TOMACS)
DiffServ node with join minimum cost queue policy and multiclass traffic
Performance Evaluation - Internet performance symposium (IPS 2002)
Join Minimum Cost Queue For Multiclass Customers: Stability And Performance Bounds
Probability in the Engineering and Informational Sciences
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Pricing Communication Networks: Economics, Technology and Modelling (Wiley Interscience Series in Systems and Optimization)
Adaptive Newton-based multivariate smoothed functional algorithms for simulation optimization
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Dynamic Programming and Optimal Control, Vol. II
Dynamic Programming and Optimal Control, Vol. II
A probabilistic constrained nonlinear optimization framework to optimize RED parameters
Performance Evaluation
Optimal multiclass internet pricing with game theoretical approach
ICOIN'09 Proceedings of the 23rd international conference on Information Networking
A proof of convergence of the B-RED and P-RED algorithms for random early detection
IEEE Communications Letters
An optimal weighted-average congestion based pricing scheme for enhanced QoS
ICDCIT'07 Proceedings of the 4th international conference on Distributed computing and internet technology
Charge-based control of DiffServ-like queues
Automatica (Journal of IFAC)
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Pricing is an effective tool to control congestion and achieve quality of service (QoS) provisioning for multiple differentiated levels of service. In this paper, we consider the problem of pricing for congestion control in the case of a network of nodes with multiple queues and multiple grades of service. We present a closed-loop multi-layered pricing scheme and propose an algorithm for finding the optimal state dependent price levels for individual queues, at each node. This is different from most adaptive pricing schemes in the literature that do not obtain a closed-loop state dependent pricing policy. The method that we propose finds optimal price levels that are functions of the queue lengths at individual queues. Further, we also propose a variant of the above scheme that assigns prices to incoming packets at each node according to a weighted average queue length at that node. This is done to reduce frequent price variations and is in the spirit of the random early detection (RED) mechanism used in TCP/IP networks. We observe in our numerical results a considerable improvement in performance using both of our schemes over that of a recently proposed related scheme in terms of both throughput and delay performance. In particular, our first scheme exhibits a throughput improvement in the range of 67-82% among all routes over the above scheme.