OpenFlow Multi-Table Lookup Architecture for Multi-Gigabit Software Defined Networking (SDN)

The proposed multi-table lookup architecture provides SDN-based, high-performance packet classification in an OpenFlow v1.1+ SDN switch. The objective of the demonstration is to show the functionality of the architecture deployed on the NetFPGA SUME Platform.

Stochastic models for regulatory networks of the genetic toggle switch

Bistability arises within a wide range of biological systems from the λ phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks.

Essays on Risk Modeling. Applications to Portfolio and Risk Management (summary section only)

In this thesis we deal with the concept of risk. The objective is to bring together and conclude on some normative information regarding quantitative portfolio management and risk assessment. The first essay concentrates on return dependency. We propose an algorithm for classifying markets into rising and falling. Given the algorithm, we derive a statistic: the Trend Switch Probability, for detection of long-term return dependency in the first moment. The empirical results suggest that the Trend Switch Probability is robust over various volatility specifications. The serial dependency in bear and bull markets behaves however differently. It is strongly positive in rising market whereas in bear markets it is closer to a random walk. Realized volatility, a technique for estimating volatility from high frequency data, is investigated in essays two and three. In the second essay we find, when measuring realized variance on a set of German stocks, that the second moment dependency structure is highly unstable and changes randomly. Results also suggest that volatility is non-stationary from time to time. In the third essay we examine the impact from market microstructure on the error between estimated realized volatility and the volatility of the underlying process. With simulation-based techniques we show that autocorrelation in returns leads to biased variance estimates and that lower sampling frequency and non-constant volatility increases the error variation between the estimated variance and the variance of the underlying process. From these essays we can conclude that volatility is not easily estimated, even from high frequency data. It is neither very well behaved in terms of stability nor dependency over time. Based on these observations, we would recommend the use of simple, transparent methods that are likely to be more robust over differing volatility regimes than models with a complex parameter universe. In analyzing long-term return dependency in the first moment we find that the Trend Switch Probability is a robust estimator. This is an interesting area for further research, with important implications for active asset allocation.

Switching and release dynamics of an electrostatically actuated MEMS switch under the influence of squeeze-film damping

This paper reports analytical modeling, simulation and experimental validation for switching and release times of an electrostatically actuated micromachined switch. Presented work is an extension of our earlier work [1] that analytically argued, and numerically and experimentally demonstrated, why pull-in time is larger that pull-up time when the actuation voltage is less than twice of the pull-in voltage. In this paper, switching dynamics is investigated under the influence of squeeze-film damping. Tests were performed on SOI (silicon-on-insulator) based parallel beams structures.Typical voltage requirement for actuation is in the range of 10-30 V. All the experiments were performed in normal atmospheric pressure. Measurement results confirm that the quality factor Q has appreciable effect on the release time compared to the switching time. The quality factor Q is extracted from the response measurement and compared with the ANSYS simulation result. In addition, the dynamic pull-in effect has also been studied and reported in this paper. A contribution of this work includes the effect of various phenomena such as squeeze-film damping, dynamic pull-in, and frequency pull-in effects on the switching dynamics of a MEMS switch.

Semi-analytic slope delay model for CMOS switch-level timing verification

A novel slope delay model for CMOS switch-level timing verification is presented. It differs from conventional methods in being semianalytic in character. The model assumes that all input waveforms are trapezoidal in overall shape, but that they vary in their slope. This simplification is quite reasonable and does not seriously affect precision, but it facilitates rapid solution. The model divides the stages in a switch-level circuit into two types. One corresponds to the logic gates, and the other corresponds to logic gates with pass transistors connected to their outputs. Semianalytic modeling for both cases is discussed.

Improving response speed of electrooptical switch in silicon-on-insulator by modifying modulation area structure

This paper reports on the simulation of two 2 x 2 electrooptical switches with different modulation area structures in silicon-on-insulator (SOI). A two-dimensional (2D) semiconductor device simulation tool PISCES-II has been used to analyze the dc and transient behaviors of the two devices. The modeling results show that the switch with an N+-I-P+-I-N+ modulation structure has a much faster response speed than the device with a P+-I-N+ modulation structure, although the former requires slightly stronger injection power.

Modeling the effect of lead-free soldering on flexible substrates

Flexible Circuit Boards (FPCs) are now being widely used in the electronic industries especially in the areas of electronic packages. Due to European lead-free legislation which has been implemented since July 2006, electronic packaging industries have to switch to use in the lead-free soldering technology. This change has posed a number of challenges in terms of development of lead-free solders and compatible substrates. An increase of at least 20-50 degrees in the reflow temperature is a concern and substantial research is required to investigate a sustainable design of flexible circuit boards as carrier substrates. This paper investigates a number of design variables such as copper conductor width, type of substrate materials, effect of insulating materials, etc. Computer modeling has been used to investigate thermo-mechanical behavior, and reliability, of flexible substrates after they have been subjected to a lead- free solder processing. Results will show particular designs that behave better for a particular rise in peak reflow temperature. Also presented will be the types of failures that can occur in these substrates and what particular materials are more reliable.

Switched Diversity Techniques for Indoor Off-body Communications Channels: An Experimental Analysis and Modeling

This paper investigates the potential improvement in signal reliability for indoor off-body communications channels operating at 5.8 GHz using switched diversity techniques. In particular we investigate the performance of switch-and-stay combining (SSC), switch-and-examine combining (SEC) and switch-and-examine combining with post-examining selection (SECps) schemes which utilize multiple spatially separated antennas at the base station. During the measurements a test subject, wearing an antenna on his chest, performed a number of walking movements towards and then away from a uniform linear array. It was found that all of the considered diversity schemes provided a worthwhile signal improvement. However, the performance of the diversity systems varied according to the switching threshold that was adopted. To model the fading envelope observed at the output of each of the combiners, we have applied diversity specific equations developed under the assumption of Nakagami-$m$ fading. As a measure of the goodness-of-fit, the Kullback-Leibler divergence between the empirical and theoretical probability density functions (PDFs) was calculated and found to be close to 0. To assist with the interpretation of the goodness-of-fit achieved in this study, the standard deviation, $\sigma$, of a zero-mean, $\sigma^2$ variance Gaussian PDF used to approximate a zero-mean, unit variance Gaussian PDF is also presented. These were generally quite close to 1 indicating that the theoretical models provided an adequate fit to the measured data.

Development and evolution of caste dimorphism in honeybees - a modeling approach

The difference in phenotypes of queens and workers is a hallmark of the highly eusocial insects. The caste dimorphism is often described as a switch-controlled polyphenism, in which environmental conditions decide an individual's caste. Using theoretical modeling and empirical data from honeybees, we show that there is no discrete larval developmental switch. Instead, a combination of larval developmental plasticity and nurse worker feeding behavior make up a colony-level social and physiological system that regulates development and produces the caste dimorphism. Discrete queen and worker phenotypes are the result of discrete feeding regimes imposed by nurses, whereas a range of experimental feeding regimes produces a continuous range of phenotypes. Worker ovariole numbers are reduced through feeding-regime-mediated reduction in juvenile hormone titers, involving reduced sugar in the larval food. Based on the mechanisms identified in our analysis, we propose a scenario of the evolutionary history of honeybee development and feeding regimes.

Piano di controllo SDN per la composizione dinamica di funzioni di rete virtuali

Il documento analizza i vantaggi introdotti nel mondo delle telecomunicazioni dai paradigmi di Software Defined Networking e Network Functions Virtualization: questi nuovi approcci permettono di creare reti programmabili e dinamiche, mantenendo alte le prestazioni. L’obiettivo finale è quello di capire se tramite la generalizzazione del codice del controller SDN , il dispositivo programmabile che permette di gestire gli switch OpenFlow, e la virtualizzazione delle reti, si possa risolvere il problema dell’ossificazione della rete Internet.

Stochastic models for regulatory networks of the genetic toggle switch

Bistability arises within a wide range of biological systems from the A phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. in this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks.