The structure and management of service level agreements innetworks

The paper proposes a structure for quality-of-service (QoS)-centered service level agreements (SLA), and a framework for their real-time management in multiservice packet networks. The SLA is structured to be fair to both parties, the service provider and their customer. The SLA considered here are for QoS assured delivery of aggregate bandwidth from ingress to egress nodes; however, the control and signaling is for the more granular flows or calls. A SLA monitoring scheme is presented in which revenue is generated by the admission of flows into the network, and penalty incurred when flows are lost in periods when the service provider is not SLA compliant. In the SLA management scheme proposed, the results of a prior off-line design are used, in conjunction with measurements taken locally at ingress nodes, to classify the loading status of routes. The routing and resource management are based on virtual partitioning and its supporting mechanism of bandwidth protection. The effectiveness of SLA management is measured by the robustness in performance in the presence of substantial diversity in actual traffic conditions. A simulation testbed called D'ARTAGNAN has been built from which we report numerical results for a case study. The results show that the SLA management scheme is robust, fair and efficient over a broad range of traffic conditions     

Computing hysteresis points of nonlinear equations depending on two parameters

A direct method is described for computing a hysteresis point (double turning point) corresponding to a cusp point of a system ofn nonlinear equations inn variables depending on two parameters. By addition of two equations a minimally extended system ofn+2 nonlinear equations is constructed for which the hysteresis point is an isolated solution. An efficient implementation of Newton's method is presented not requiring evaluations of second derivatives of the original problem. Two numerical examples show the efficiency of theQ-quadratically convergent method.     

An artificial neural network approach on parametric optimization of laser micro-machining of die-steel

In the present research, laser micro machining (LMM) of tungsten-molybdenum general purpose high speed steel (Rex M2) has been studied. Selection of optimum machining parameter combinations for obtaining higher depth of groove and smaller height of recast layer is a challenging task in LMM due to the presence of a large number of process variables. There is no perfect combination of parameters which can simultaneously result in both the highest depth of groove and lowest height of recast layer. This paper presents an attempt to develop a strategy for predicting the optimum machining parameter setting for the generation of the maximum depth of groove with minimum height of recast layer. A feed forward back-propagation neural network has been developed to model the machining process. The model, after proper training, is capable of predicting the response parameters as a function of four different control parameters. Experimental results demonstrate that the machining model is suitable and the optimization strategy satisfies practical requirements. The developed model has been found to be quite unique, powerful and flexible.     

Modified CMA based blind multiuser equaliser with decision directed scheme

A modified constant modulus (CM) algorithm based blind multiuser equaliser with a decision directed (DD) scheme is developed that does not require any mutual decorrelation and is suitable for downlink direct sequence code division multiple access systems. The performance of the proposed time domain adaptive equaliser is evaluated with respect to usual parameters and is found to perform better than the concurrent CM algorithm and DD scheme.