An algorithm for dynamic optimal bandwidth allocation in communication networks

We study the problem of optimal bandwidth allocation in communication networks. We consider a queueing model with two queues to which traffic from different competing flows arrive. The queue length at the buffers is observed every T instants of time, on the basis of which a decision on the amount of bandwidth to be allocated to each buffer for the next T instants is made. We consider a class of closed-loop feedback policies for the system and use a twotimescale simultaneous perturbation stochastic approximation(SPSA) algorithm to find an optimal policy within the prescribed class. We study the performance of the proposed algorithm on a numerical setting. Our algorithm is found to exhibit good performance.

Dynamic Supply and Threshold Voltage Scaling for CMOS Digital Circuits Using In-Situ Power Monitor

A generalized power tracking algorithm that minimizes power consumption of digital circuits by dynamic control of supply voltage and the body bias is proposed. A direct power monitoring scheme is proposed that does not need any replica and hence can sense total power consumed by load circuit across process, voltage, and temperature corners. Design details and performance of power monitor and tracking algorithm are examined by a simulation framework developed using UMC 90-nm CMOS triple well process. The proposed algorithm with direct power monitor achieves a power savings of 42.2% for activity of 0.02 and 22.4% for activity of 0.04. Experimental results from test chip fabricated in AMS 350 nm process shows power savings of 46.3% and 65% for load circuit operating in super threshold and near sub-threshold region, respectively. Measured resolution of power monitor is around 0.25 mV and it has a power overhead of 2.2% of die power. Issues with loop convergence and design tradeoff for power monitor are also discussed in this paper.

Dynamic Supply and Threshold Voltage Scaling for CMOS Digital Circuits Using In-Situ Power Monitor

A generalized power tracking algorithm that minimizes power consumption of digital circuits by dynamic control of supply voltage and the body bias is proposed. A direct power monitoring scheme is proposed that does not need any replica and hence can sense total power consumed by load circuit across process, voltage, and temperature corners. Design details and performance of power monitor and tracking algorithm are examined by a simulation framework developed using UMC 90-nm CMOS triple well process. The proposed algorithm with direct power monitor achieves a power savings of 42.2% for activity of 0.02 and 22.4% for activity of 0.04. Experimental results from test chip fabricated in AMS 350 nm process shows power savings of 46.3% and 65% for load circuit operating in super threshold and near sub-threshold region, respectively. Measured resolution of power monitor is around 0.25 mV and it has a power overhead of 2.2% of die power. Issues with loop convergence and design tradeoff for power monitor are also discussed in this paper.

Microelectromechanical torsional varactors with low parasitic capacitances and high dynamic range

This work focuses on the design of torsional microelectromechanical systems (MEMS) varactors to achieve highdynamic range of capacitances. MEMS varactors fabricated through the polyMUMPS process are characterized at low and high frequencies for their capacitance-voltage characteristics and electrical parasitics. The effect of parasitic capacitances on tuning ratio is studied and an equivalent circuit is developed. Two variants of torsional varactors that help to improve the dynamic range of torsional varactors despite the parasitics are proposed and characterized. A tuning ratio of 1:8, which is the highest reported in literature, has been obtained. We also demonstrate through simulations that much higher tuning ratios can be obtained with the designs proposed. The designs and experimental results presented are relevant to CMOS fabrication processes that use low resistivity substrate. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). DOI: 10.1117/1.JMM.11.1.013006]

Performance of inherently compensated flat pad aerostatic bearings subject to dynamic perturbation forces

The importance of air bearing design is growing in engineering. As the trend to precision and ultra precision manufacture gains pace and the drive to higher quality and more reliable products continues, the advantages which can be gained from applying aerostatic bearings to machine tools, instrumentation and test rigs is becoming more apparent. The inlet restrictor design is significant for air bearings because it affects the static and dynamic performance of the air bearing. For instance pocketed orifice bearings give higher load capacity as compared to inherently compensated orifice type bearings, however inherently compensated orifices, also known as laminar flow restrictors are known to give highly stable air bearing systems (less prone to pneumatic hammer) as compared to pocketed orifice air bearing systems. However, they are not commonly used because of the difficulties encountered in manufacturing and assembly of the orifice designs. This paper aims to analyse the static and dynamic characteristics of inherently compensated orifice based flat pad air bearing system. Based on Reynolds equation and mass conservation equation for incompressible flow, the steady state characteristics are studied while the dynamic state characteristics are performed in a similar manner however, using the above equations for compressible flow. Steady state experiments were also performed for a single orifice air bearing and the results are compared to that obtained from theoretical studies. A technique to ease the assembly of orifices with the air bearing plate has also been discussed so as to make the manufacturing of the inherently compensated bearings more commercially viable. (c) 2012 Elsevier Inc. All rights reserved.

Nonlinear dynamic state estimation in instrumented structures with conditionally linear Gaussian substructures

Many problems of state estimation in structural dynamics permit a partitioning of system states into nonlinear and conditionally linear substructures. This enables a part of the problem to be solved exactly, using the Kalman filter, and the remainder using Monte Carlo simulations. The present study develops an algorithm that combines sequential importance sampling based particle filtering with Kalman filtering to a fairly general form of process equations and demonstrates the application of a substructuring scheme to problems of hidden state estimation in structures with local nonlinearities, response sensitivity model updating in nonlinear systems, and characterization of residual displacements in instrumented inelastic structures. The paper also theoretically demonstrates that the sampling variance associated with the substructuring scheme used does not exceed the sampling variance corresponding to the Monte Carlo filtering without substructuring. (C) 2012 Elsevier Ltd. All rights reserved.

Integrated magnetics based multi-port bidirectional DC-DC converter topology for discontinuous-mode operation

A new type of multi-port isolated bidirectional DC-DC converter is proposed in this study. In the proposed converter, transfer of power takes place through addition of magnetomotive forces generated by multiple windings on a common transformer core. This eliminates the need for a centralised storage capacitor to interface all the ports. Hence, the requirement of an additional power transfer stage from the centralised capacitor can also be eliminated. The converter can be used for a multi-input, multi-output (MIMO) system. A pulse width modulation (PWM) strategy for controlling simultaneous power flow in the MIMO converter is also proposed. The proposed PWM scheme works in the discontinuous conduction mode. The leakage inductance can be chosen to aid power transfer. By using the proposed converter topology and PWM scheme, the need to compute power flow equations to determine the magnitude and direction of power flow between ports is alleviated. Instead, a simple controller structure based on average current control can be used to control the power flow. This study discusses the operating phases of the proposed multi-port converter along with its PWM scheme, the design process for each of the ports and finally experimental waveforms that validate the multi-port scheme.

Evaluation of dynamic voltage and frequency scaling for stream programs

Dynamic Voltage and Frequency Scaling (DVFS) offers a huge potential for designing trade-offs involving energy, power, temperature and performance of computing systems. In this paper, we evaluate three different DVFS schemes - our enhancement of a Petri net performance model based DVFS method for sequential programs to stream programs, a simple profile based Linear Scaling method, and an existing hardware based DVFS method for multithreaded applications - using multithreaded stream applications, in a full system Chip Multiprocessor (CMP) simulator. From our evaluation, we find that the software based methods achieve significant Energy/Throughput2(ET−2) improvements. The hardware based scheme degrades performance heavily and suffers ET−2 loss. Our results indicate that the simple profile based scheme achieves the benefits of the complex Petri net based scheme for stream programs, and present a strong case for the need for independent voltage/frequency control for different cores of CMPs, which is lacking in most of the state-of-the-art CMPs. This is in contrast to the conclusions of a recent evaluation of per-core DVFS schemes for multithreaded applications for CMPs.

A dynamic topology management in a hybrid wireless superstore network

with the development of large scale wireless networks, there has been short comings and limitations in traditional network topology management systems. In this paper, an adaptive algorithm is proposed to maintain topology of hybrid wireless superstore network by considering the transactions and individual network load. The adaptations include to choose the best network connection for the response, and to perform network Connection switching when network situation changes. At the same time, in terms of the design for topology management systems, aiming at intelligence, real-time, the study makes a step-by-step argument and research on the overall topology management scheme. Architecture for the adaptive topology management of hybrid wireless networking resources is available to user’s mobile device. Simulation results describes that the new scheme has outperformed the original topology management and it is simpler than the original rate borrowing scheme.

Time variant reliability model updating in instrumented dynamical systems based on Girsanov's transformation

The problem of updating the reliability of instrumented structures based on measured response under random dynamic loading is considered. A solution strategy within the framework of Monte Carlo simulation based dynamic state estimation method and Girsanov's transformation for variance reduction is developed. For linear Gaussian state space models, the solution is developed based on continuous version of the Kalman filter, while, for non-linear and (or) non-Gaussian state space models, bootstrap particle filters are adopted. The controls to implement the Girsanov transformation are developed by solving a constrained non-linear optimization problem. Numerical illustrations include studies on a multi degree of freedom linear system and non-linear systems with geometric and (or) hereditary non-linearities and non-stationary random excitations.

Analysis of voltage stability in multi-infeed HVDC systems with STATCOM

This paper presents the modelling and analysis of voltage stability at AC commutation bus in LCC (Line commutated converters) based multi-infeed HVDC system. The paper also presents the analysis of effects of various operating control modes in HVDC as well as location of disturbance on the voltage stability of the system under study. A new method of modelling the LCC converters as time varying admittance at the AC commutation bus is also presented in this paper. In this paper, the modelling of STATCOM for provision of dynamic voltage support at one of the AC buses of the HVDC system is presented. The reactive power injected by STATCOM is controlled by regulating the voltage of the AC bus to which STATCOM is connected. The case study also discusses the effects of various possible combinations of location of STATCOM and disturbance considered, on the voltage stability of the multi-infeed HVDC system.

Time variant reliability model updating in instrumented dynamical systems based on Girsanov’s transformation

The problem of updating the reliability of instrumented structures based on measured response under random dynamic loading is considered. A solution strategy within the framework of Monte Carlo simulation based dynamic state estimation method and Girsanov’s transformation for variance reduction is developed. For linear Gaussian state space models, the solution is developed based on continuous version of the Kalman filter, while, for non-linear and (or) non-Gaussian state space models, bootstrap particle filters are adopted. The controls to implement the Girsanov transformation are developed by solving a constrained non-linear optimization problem. Numerical illustrations include studies on a multi degree of freedom linear system and non-linear systems with geometric and (or) hereditary non-linearities and non-stationary random excitations.

Dynamic state estimation for identifying earthquake support motions in instrumented structures

The problem of identification of multi-component and (or) spatially varying earthquake support motions based on measured responses in instrumented structures is considered. The governing equations of motion are cast in the state space form and a time domain solution to the input identification problem is developed based on the Kalman and particle filtering methods. The method allows for noise in measured responses, imperfections in mathematical model for the structure, and possible nonlinear behavior of the structure. The unknown support motions are treated as hypothetical additional system states and a prior model for these motions are taken to be given in terms of white noise processes. For linear systems, the solution is developed within the Kalman filtering framework while, for nonlinear systems, the Monte Carlo simulation based particle filtering tools are employed. In the latter case, the question of controlling sampling variance based on the idea of Rao-Blackwellization is also explored. Illustrative examples include identification of multi-component and spatially varying support motions in linear/nonlinear structures.

Network, nodes and nexus: systems approach to multitarget therapeutics

Systems biology is revealing multiple layers of regulatory networks that manifest spatiotemporal variations. Since genes and environment also influence the emergent property of a cell, the biological output requires dynamic understanding of various molecular circuitries. The metabolic networks continually adapt and evolve to cope with the changing milieu of the system, which could also include infection by another organism. Such perturbations of the functional networks can result in disease phenotypes, for instance tuberculosis and cancer. In order to develop effective therapeutics, it is important to determine the disease progression profiles of complex disorders that can reveal dynamic aspects and to develop mutitarget systemic therapies that can help overcome pathway adaptations and redundancy.

Study of dynamic behaviour of recession curves

Since Brutsaert and Neiber (1977), recession curves are widely used to analyse subsurface systems of river basins by expressing -dQ/dt as a function of Q, which typically take a power law form: -dQ/dt=kQ, where Q is the discharge at a basin outlet at time t. Traditionally recession flows are modelled by single reservoir models that assume a unique relationship between -dQ/dt and Q for a basin. However, recent observations indicate that -dQ/dt-Q relationship of a basin varies greatly across recession events, indicating the limitation of such models. In this study, the dynamic relationship between -dQ/dt and Q of a basin is investigated through the geomorphological recession flow model which models recession flows by considering the temporal evolution of its active drainage network (the part of the stream network of the basin draining water at time t). Two primary factors responsible for the dynamic relationship are identified: (i) degree of aquifer recharge (ii) spatial variation of rainfall. Degree of aquifer recharge, which is likely to be controlled by (effective) rainfall patterns, influences the power law coefficient, k. It is found that k has correlation with past average streamflow, which confirms the notion that dynamic -dQ/dt-Q relationship is caused by the degree of aquifer recharge. Spatial variation of rainfall is found to have control on both the exponent, , and the power law coefficient, k. It is noticed that that even with same and k, recession curves can be different, possibly due to their different (recession) peak values. This may also happen due to spatial variation of rainfall. Copyright (c) 2012 John Wiley & Sons, Ltd.