Intelligent Monitoring for Adaptation in Grid Applications

Grid applications access distributed, and often shared, resources. One consequence of this resource sharing is that measured application performance can vary widely and in unexpected ways. Determining the causes of poor performance, due to either anomalous application behavior or contention for shared resource use, and adapting to changing circumstances are critical to creation of robust Grid applications. Performance contracts and real-time adaptive control are two mechanisms to realize soft performance guarantees in Grid environments. Performance contracts formalize the relationship between application performance needs and resource capabilities. During execution, contract monitors use performance data to verify that expectations are met. When the contracted specifications are not satisfied, the system can choose to either adapt the application to available resources or reschedule the application on a new set of resources that can satisfy the original contract specifications. We describe an infrastructure for Grid application contract development and monitoring. This infrastructure, based on the Autopilot toolkit, provides flexible and scalable tools to assess both application and system behavior.     

Widely tunable bottom-emitting vertical-cavity SOAs

We present bottom-emitting tunable vertical-cavity semiconductor optical amplifiers (VCSOAs) with an effective wavelength tuning range of >20 nm. These devices utilize a high reflectivity micromechanically tunable Bragg mirror as the back reflector. Compared with our first generation tunable VCSOAs, the bottom-emitting devices exhibit a two-fold increase in the effective tuning range as well as a five-fold reduction in the required tuning voltage.     

Novel T-rail electrodes for substrate removed low-voltage high-speed GaAs/AlGaAs electrooptic modulators

A novel traveling-wave electrode utilizing capacitively loaded T-rail elements was developed for low-voltage high-speed substrate-removed GaAs/AlGaAs electrooptic modulators. Electrodes with varying dimensions were fabricated and characterized. Electrode phase velocity, characteristic impedance, loss coefficient, and capacitive loading were extracted from the measured s-parameters up to 40 GHz. Electrode was also simulated using a finite-element solver. The measured and calculated electrode capacitance values were found to be in excellent agreement, showing that the electrode can be precisely designed. Approaches were outlined to provide a group velocity-matched very high-speed modulator electrode suitable for a low drive-voltage substrate-removed GaAs/AlGaAs electro-optic modulator     

Fuzzy Learning of Talbot Effect Guides Optimal Mask Design for Proximity Field Nanopatterning Lithography

Processing methods used in photonics and nanotechnology possess many limitations restricting their application areas such as high cost, inability to produce fine details, problems with scalability, and long processing time. Proximity field nanopatterning is a lithography method which surpasses these limitations. By using interference patterns produced by a two-dimensional phase mask, the technique is able to generate a submicron detailed exposure on a millimeter-size slab of light sensitive photopolymer, which is then developed like a photographic plate to reveal three-dimensional interference patterns from the phase mask. While it is possible to use simulations to obtain the interference patterns produced by a phase mask, realizing the mask dimensions necessary for producing a desired interference pattern is analytically challenging due to the intricacies of light interactions involved in producing the final interference pattern. An alternative method is to iteratively optimize the phase mask until the interference patterns obtained converge to the desired pattern. However, depending on the optimization technique used, one either risks a significant probability of failure or requires a prohibitive number of iterations. We argue that an optimization technique that is to take advantage of the physics of the problem using machine learning methods (here fuzzy learning) can lead to competent mask design. This technique is described in this letter.     

A 0.9 V 92 dB Double-Sampled Switched-RC Delta-Sigma Audio ADC

A 0.9 V third-order double-sampled delta-sigma audio ADC is presented. A new method using a combination of a switched-RC technique and a floating switched-capacitor double-sampling configuration enabled low-voltage operation without clock boosting or bootstrapping. A three-level quantizer with simple dynamic element matching was used to improve linearity. The prototype IC implemented in a 0.13 CMOS process achieves 92 dB DR, 91 dB SNR and 89 dB SNDR in a 24 kHz audio signal bandwidth, while consuming 1.5 mW from a 0.9 V supply. The prototype operates from 0.65 V to 1.5 V supply with minimal performance degradation.     

Equilibrium Problems with Applications to Eigenvalue Problems

In this paper, we consider equilibrium problems and introduce the concept of (S)₊ condition for bifunctions. Existence results for equilibrium problems with the (S)₊ condition are derived. As special cases, we obtain several existence results for the generalized nonlinear variational inequality studied by Ding and Tarafdar (Ref. 1) and the generalized variational inequality studied by Cubiotti and Yao (Ref. 2). Finally, applications to a class of eigenvalue problems are given.