General QoS-Aware Scheduling Procedure for Passive Optical Networks

Increasing volume, dynamism, and diversity of access traffic have complicated the challenging problem of dynamic resource allocation in passive optical networks. We introduce a general scheduling procedure for passive optical networks, which optimizes a desired performance metric for an arbitrary set of operational constraints. The proposed scheduling has a fast and causal iterative implementation, where each iteration involves a local optimization problem followed by a recursive update of some status information. The generality of the platform enables a proper description of the diverse quality of service requirements, while its low computational complexity makes agile tracking of the network dynamism possible. To demonstrate its versatility and generality, the applications of the scheme for service-differentiated dynamic bandwidth allocation in time- and wavelength-division-multiplexed passive optical networks are discussed. To further reduce the computational complexity, a closed-form solution of the involved optimization in each iteration of the scheduling is derived. We directly incorporate transmission delay in the scheduling and show how the consumed power is traded for the tolerable amount of transmission delay. Furthermore, a 50% power efficiency improvement is reported by exploiting the inherent service diversity among subscribers. The impact of service prioritization, finite buffer length, and packet drops on the power efficiency of the scheme are also investigated

Gradient, non-gradient and hybrid algorithms for optimizing 3D forging sequences with uncertainties

Reprinted with permission from AIP Conf. Proc May 17, 2007 Volume 908, pp. 475-480 MATERIALS PROCESSING AND DESIGN; Modeling, Simulation and Applications; NUMIFORM '07; Proceedings of the 9th International Conference on Numerical Methods in Industrial Forming Processes; doi:10.1063/1.2740856. Copyright 2007 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of PhysicsInternational audienceIn the frame of computationally expensive 3D metal forming simulations, optimization algorithms are studied in order to find satisfactory solutions within less than 50 simulations and to handle complex optimizations problems with several extrema. Two types of algorithms are selected, which both utilize a meta-model to approximate the objective function and so reduce computational cost. This model either supports standard Evolutionary Algorithms, such as Genetic Algorithms, or is sequentially improved until finding a satisfactory and well approximated solution. The Meshless Finite Difference Method is the utilized meta-model, without (standard algorithm) or with (hybrid algorithm) the gradient information. This meta-model approach allows taking into account uncertainties on optimization parameters in an inexpensive way. The optimization procedure is modified accordingly. The proposed algorithms are first evaluated and compared on standard analytic functions, and then applied to a 3D forging benchmark, the shape optimization of preform tool in order to minimize the potential of fold formation

On the Selection of Tuning Methodology of FOPID Controllers for the Control of Higher Order Processes

In this paper, a comparative study is done on the time and frequency domain tuning strategies for fractional order (FO) PID controllers to handle higher order processes. A new fractional order template for reduced parameter modeling of stable minimum/non-minimum phase higher order processes is introduced and its advantage in frequency domain tuning of FOPID controllers is also presented. The time domain optimal tuning of FOPID controllers have also been carried out to handle these higher order processes by performing optimization with various integral performance indices. The paper highlights on the practical control system implementation issues like flexibility of online autotuning, reduced control signal and actuator size, capability of measurement noise filtration, load disturbance suppression, robustness against parameter uncertainties etc. in light of the above tuning methodologies.Comment: 27 pages, 10 figure