One of the more challenging and unresolved issues in ATM networks is the congestion control of available bit rate （ABR）. The dynamic controller is designed based on the control theory and the feedback mechanism of explicit rates With the given method of a chosen parameter, it can guarantee the stability of the controller and closed loop system with propagation delay and bandwidth oscillation. It needs less parameters（only one） to be designed. The queue length can converge to the given value in the least steps. The fairness of different connections is considered further. The simulations show better performance and good quality of service（QoS） is achieved.
In this paper,we apply adaptive coded modulation (ACM) schemes to a wireless networked control system (WNCS) to improve the energy efficiency and increase the data rate over a fading channel.To capture the characteristics of varying rate, interference,and routing in wireless transmission channels,the concepts of equivalent delay (ED) and networked condition index (NCI) are introduced.Also,the analytic lower and upper bounds of EDs are obtained.Furthermore,we model the WNCS as a multicontroller switched system (MSS) under consideration of EDs and loss index in the wireless transmission.Sufficient stability condition of the closed-loop WNCS and corresponding dynamic state feedback controllers are derived in terms of linear matrix inequality (LMI). Numerical results show the validity and advantage of our proposed control strategies.
We consider the problem of fair rate control for wireless ad-hoc networks with time varying channel capacities. The interaction between links in wireless ad-hoc networks introduces additional constraints on the flow rate. A primal-dual algorithm that guarantees fair rate control is proved to be trajectory stable. Various fairness indexes are obtained by choosing the specified form of the utility functions, and the numerical results validate the effectiveness of the proposed algorithm.
The margin maximization problem in digital subscriber line（DSL） systems is investigated.The particle swarm optimization（PSO） theory is applied to the nonconvex margin optimization problem with the target power and rate constraints.PSO is a new evolution algorithm based on the social behavior of swarms, which can solve discontinuous, nonconvex and nonlinear problems efficiently.The proposed algorithm can converge to the global optimal solution, and numerical example demonstrates that the proposed algorithm can guarantee the fast convergence within a few iterations.
