TINA — A Distributed Approach to Service Management

The Telecommunications Information Networking Architecture Consortium (TINA-C) was formed 5 years ago to develop an architecture to address the radical business and technological changes then envisaged in the future telecommunications world. Central to the proposed solution is an infrastructure known as the TINA distributed processing environment (DPE). The TINA service architecture, which defines a set of concepts and rules for the management of a wide range of services, is of particular interest here. This paper outlines the current status and output of the TINA Consortium and goes on to describe a collaborative implementation project which uses many of the TINA concepts and specifications to build a pan-European service platform. An important vision within TINA is that of open interfaces and interoperability in a heterogeneous environment. The extent to which this goal has been achieved is discussed in the light of experience.     

Model-driven systems development and integration environment

Telecommunications operators are undergoing massive transformations in order to metamorphose themselves into the ICT world and compete with agile, lean IT organisations. The main challenges facing telecommunications operators, such as BT, are to reduce costs and increase agility in deploying software systems for provisioning ICT services. Despite using reusable capabilities and COTS packages, the major source of increased cost lies in the heavy integration tax we incur for integrating diverse systems implemented on diverse platforms and middleware, with heterogeneous data and process models. This paper looks at cost implications of lengthy and often manual migration to-and-from systems and platforms, and shows the clear business benefits of model-driven development (MDD) as defined by the Object Management Group (OMG). It is clearly demonstrated that model-driven development has matured into a practical, industrialised, scalable and evolvable technology, culminating from decades of R&D on specification and design languages, executable formalisms and domainspecific languages and language transformations.     

A 10-GB/s SONET-compliant CMOS transceiver with low crosstalk and intrinsic jitter

A 4:1 SERDES IC suitable for SONET OC-192 and 10-Gb/s Ethernet is presented. The receiver, which consists of a limiting amplifier, a clock and data recovery unit, and a demultiplexer, locks automatically to all data rates in the range 9.95-10.7 Gb/s. At a bit error rate of less than 10/sup -12/, it has a sensitivity of 20 mV. The transmitter comprises a clock multiplying unit and a multiplexer. The jitter of the transmitted data signal is 0.2 ps RMS. This is facilitated by a novel notched inductor layout and a special power supply concept, which reduces cross-coupling between the transmitter and receiver. Integrated in a 0.13-/spl mu/m CMOS technology, the total power consumption from both 1.2- and 2.5-V supplies is less than 1 W.     

A reliable overlay video transport protocol for multicast agents in wireless mesh networks

A new video transport protocol for multicast agents in wireless mesh networks (WMNs) is proposed in this paper. The proposed protocol enables a significant reduction in the transmission overhead, while providing reliable communication for its use in multicast applications. This proposed reliable protocol provides a practical approach for an overlay peer‐to‐peer multicast facility supported within the application layer. This obviates the need to give upgraded routers capable of handling multicast broadcasting or modify the existing protocol stack. The protocol tolerates partial losses in multimedia transmissions, while supporting control of the delay sensitivity of such transmissions in WMNs. The key issue in this protocol is the ability to detect packet loss, anticipate retransmission requests, and use the anticipated retransmission requests to transmit the lost packets prior to requests from other receiving agents. The proposed protocol allows for the receiver to determine if retransmission of lost packets is required, ensuring the greatest flexibility needed for a reliable multicast protocol. Copyright © 2009 John Wiley & Sons, Ltd.     

Digital image processing-an object-oriented approach

This paper presents a class library dedicated to digital image processing which provides resources for essential digital image processing operations. Besides its practical value, the class library is used to teach both object-oriented software engineering methodology and digital image processing. The resulting module can be accessed from independent specialized applications through its public interface while its implementation details are perfectly encapsulated. First of all it is used as the inner part of an integrated environment designed for students and researchers in the field of digital image processing. This software component was built aiming for both portability and extendibility. It contains attributes and methods that allow for a wide range of digital image processing algorithms: point and geometric operations; filter, edge detection, segmentation and texture operations; and fast Fourier transforms, discrete cosine transforms, and wavelet and Gabor transformations. All these can be used for image enhancement, restoration, compression, analysis, and synthesis     

An adaptive RAM-DFE for storage channels

A modification of the decision feedback equalizer (DFE), RAM-DFE, is presented and analyzed for use in channels with trailing nonlinear intersymbol interference, especially binary saturation-recording channels. In the RAM-DFE, a look-up table, which can be easily implemented with random access memory, (RAM), replaces the transversal filter feedback section of the DFE. The feedforward section of the equalizer remains linear. A general nonlinear Markov (or finite-state machine) model is used to model the nonlinear intersymbol interference (ISI) channel. With this Markov model, a method is introduced for computing the minimum-mean-squared-error settings of the feedforward filter coefficients and the feedback filter and look-up table contents for the linear DFE and the RAM-DFE, respectively. RAM-DFE with these settings can be significantly better than the linear DFE for channels with trailing nonlinear ISI. Globally convergent gradient-type algorithms for updating the feedforward section coefficients and the contents of the feedback table are introduced and analyzed. Results based on data taken from disk storage units are discussed     

A microwave photonic phase-shifter based on wavelength conversion in a DFB laser

We propose and demonstrate a microwave photonic phase-shifter using a distributed-feedback laser-wavelength converter. Through carrier competition in the laser, information is passed from the input signal to the lasing mode. The frequency response of this conversion mechanism follows the intrinsic modulation response of the laser, which exhibits a large phase change near the relaxation frequency. Through current-control of the relaxation frequency, the phase of the wavelength-converted microwave output can be varied by more than 135/spl deg/ over a bandwidth of 1.8GHz. We further identify an operating regime that exhibits a large discrete phase shift of 114/spl deg/ at 3 GHz with negligible change in power.     

A nonparametric statistical method for image segmentation using information theory and curve evolution.

In this paper, we present a new information-theoretic approach to image segmentation. We cast the segmentation problem as the maximization of the mutual information between the region labels and the image pixel intensities, subject to a constraint on the total length of the region boundaries. We assume that the probability densities associated with the image pixel intensities within each region are completely unknown a priori, and we formulate the problem based on nonparametric density estimates. Due to the nonparametric structure, our method does not require the image regions to have a particular type of probability distribution and does not require the extraction and use of a particular statistic. We solve the information-theoretic optimization problem by deriving the associated gradient flows and applying curve evolution techniques. We use level-set methods to implement the resulting evolution. The experimental results based on both synthetic and real images demonstrate that the proposed technique can solve a variety of challenging image segmentation problems. Futhermore, our method, which does not require any training, performs as good as methods based on training.