Predictable service overlay networks: Predictability through adaptive monitoring and efficient overlay construction and management

Providing bounded communication among participating nodes is significant for distributed systems. Internet-based applications suffer with lower performance due to absence of bounded latency. We describe PSON, an overlay network solution to this challenging problem. PSON has two components. The monitoring component, SyncProbe, utilizes efficient and adaptive monitoring techniques to measure latency, detect packet loss, and provide real-time estimates of maximum expected latency along paths of an Internet substrate. The QoSMap component constructs and manages overlay such that it yields application-level QoS and provides resilience against network failures. A distinctive feature of QoSMap is construction of QoS-compliant backup paths which facilitate in overlay management and operation during the period when primary overlay paths violate QoS. We evaluate PSON on PlanetLab to provide predictable communication for applications with different topology and QoS requirement. Our experiments confirm the effectiveness of PSON in providing an inexpensive and efficient application-layer solution to Internet’s unpredictable behavior.     

Estimating postprandial glucose fluxes using hierarchical Bayes modelling

A new stochastic computational method was developed to estimate the endogenous glucose production, the meal-related glucose appearance rate (R(a meal)), and the glucose disposal (R(d)) during the meal tolerance test. A prior probability distribution was adopted which assumes smooth glucose fluxes with individualized smoothness level within the context of a Bayes hierarchical model. The new method was contrasted with the maximum likelihood method using data collected in 18 subjects with type 2 diabetes who ingested a mixed meal containing [U-(13)C]glucose. Primed [6,6-(2)H(2)]glucose was infused in a manner that mimicked the expected endogenous glucose production. The mean endogenous glucose production, R(a meal), and R(d) calculated by the new method and maximum likelihood method were nearly identical. However, the maximum likelihood gave constant, nonphysiological postprandial endogenous glucose production in two subjects whilst the new method gave plausible estimates of endogenous glucose production in all subjects. Additionally, the two methods were compared using a simulated triple-tracer experiment in 12 virtual subjects. The accuracy of the estimates of the endogenous glucose production and R(a meal) profiles was similar [root mean square error (RMSE) 1.0±0.3 vs. 1.4±0.7μmol/kg/min for EGP and 2.6±1.0 vs. 2.9±0.9μmol/kg/min for R(a meal); new method vs. maximum likelihood method; P=NS, paired t-test]. The accuracy of R(d) estimates was significantly increased by the new method (RMSE 5.3±1.9 vs. 4.2±1.3; new method vs. ML method; P<0.01, paired t-test). We conclude that the new method increases plausibility of the endogenous glucose production and improves accuracy of glucose disposal compared to the maximum likelihood method.     

A mobility constraint model to infer sensor behaviour in forest fire risk monitoring

Wireless sensor networks (WSNs) play an important role in forest fire risk monitoring. Various applications are in operation. However, the use of mobile sensors in forest risk monitoring remains largely unexplored. Our research contributes to fill this gap by designing a model which abstracts mobility constraints within different types of contexts for the inference of mobile sensor behaviour. This behaviour is focused on achieving a suitable spatial coverage of the WSN when monitoring forest fire risk. The proposed mobility constraint model makes use of a Bayesian network approach and consists of three components: (1) a context typology describing different contexts in which a WSN monitors a dynamic phenomenon; (2) a context graph encoding probabilistic dependencies among variables of interest; and (3) contextual rules encoding expert knowledge and application requirements needed for the inference of sensor behaviour. As an illustration, the model is used to simulate the behaviour of a mobile WSN to obtain a suitable spatial coverage in low and high fire risk scenarios. It is shown that the implemented Bayesian network within the mobility constraint model can successfully infer behaviour such as sleeping sensors, moving sensors, or deploying more sensors to enhance spatial coverage. Furthermore, the mobility constraint model contributes towards mobile sensing in which the mobile sensor behaviour is driven by constraints on the state of the phenomenon and the sensing system.     

Measurement technique for the thermal properties of thin-film diaphragms embedded in calorimetric flow sensors

In diaphragm-based micromachined calorimetric flow sensors, convective heat transfer through the test fluid competes with the spurious heat shunt induced by the thin-film diaphragm where heating and temperature sensing elements are embedded. Consequently, accurate knowledge of thermal conductivity, thermal diffusivity, and emissivity of the diaphragm is mandatory for design, simulation, optimization, and characterization of such devices. However, these parameters can differ considerably from those stated for bulk material and they typically depend on the production process. We developed a novel technique to extract the thermal thin-film properties directly from measurements carried out on calorimetric flow sensors. Here, the heat transfer frequency response from the heater to the spatially separated temperature sensors is measured and compared to a theoretically obtained relationship arising from an extensive two-dimensional analytical model. The model covers the heat generation by the resistive heater, the heat conduction within the diaphragm, the radiation loss at the diaphragm’s surface, and the heat sink caused by the supporting silicon frame. This contribution summarizes the analytical heat transfer analysis in the microstructure and its verification by a computer numerical model, the measurement setup, and the associated thermal parameter extraction procedure. Furthermore, we report on measurement results for the thermal conductivity, thermal diffusivity, and effective emissivity obtained from calorimetric flow sensor specimens featuring dielectric thin-film diaphragms made of plasma enhanced chemical vapor deposition silicon nitride.     

Acousto-optical PD detection for transformers

Partial discharge (PD) is one of the factors that could lead to failure of power transformers, leading to power outage and expensive repairs. The acoustic wave induced by PD can be measured and used for monitoring, diagnosing, and locating potential failures in the transformers. Fiber optic sensors have been shown to be attractive devices for PD detection because of a number of inherent advantages including small size, high sensitivity, electrical nonconductivity, and immunity to electromagnetic interference. A fiber optic sensor based on a Fabry-Perot interferometry is constructed by a simple micromachining process compatible with microelectromechanical system technology. The sensors are used in a transformer to measure PD acoustic waves. The experimental results show the sensor not only has an inherent high signal to noise capability, but is able to accurately localize the PD sources inside the transformer.     

Brain-computer interfaces for 1-D and 2-D cursor control: designs using volitional control of the EEG spectrum or steady-state visual evoked potentials.

We have developed and tested two electroencephalogram (EEG)-based brain-computer interfaces (BCI) for users to control a cursor on a computer display. Our system uses an adaptive algorithm, based on kernel partial least squares classification (KPLS), to associate patterns in multichannel EEG frequency spectra with cursor controls. Our first BCI, Target Practice, is a system for one-dimensional device control, in which participants use biofeedback to learn voluntary control of their EEG spectra. Target Practice uses a KPLS classifier to map power spectra of 62-electrode EEG signals to rightward or leftward position of a moving cursor on a computer display. Three subjects learned to control motion of a cursor on a video display in multiple blocks of 60 trials over periods of up to six weeks. The best subject's average skill in correct selection of the cursor direction grew from 58% to 88% after 13 training sessions. Target Practice also implements online control of two artifact sources: 1) removal of ocular artifact by linear subtraction of wavelet-smoothed vertical and horizontal electrooculograms (EOG) signals, 2) control of muscle artifact by inhibition of BCI training during periods of relatively high power in the 40-64 Hz band. The second BCI, Think Pointer, is a system for two-dimensional cursor control. Steady-state visual evoked potentials (SSVEP) are triggered by four flickering checkerboard stimuli located in narrow strips at each edge of the display. The user attends to one of the four beacons to initiate motion in the desired direction. The SSVEP signals are recorded from 12 electrodes located over the occipital region. A KPLS classifier is individually calibrated to map multichannel frequency bands of the SSVEP signals to right-left or up-down motion of a cursor on a computer display. The display stops moving when the user attends to a central fixation point. As for Target Practice, Think Pointer also implements wavelet-based online removal of ocular artifact; however, in Think Pointer muscle artifact is controlled via adaptive normalization of the SSVEP. Training of the classifier requires about 3 min. We have tested our system in real-time operation in three human subjects. Across subjects and sessions, control accuracy ranged from 80% to 100% correct with lags of 1-5 s for movement initiation and turning. We have also developed a realistic demonstration of our system for control of a moving map display (http://ti.arc.nasa.gov/).     

Secure Sharing of Tuple Spaces in Ad Hoc Settings

Security is emerging as a growing concern throughout the distributed computing community. Typical solutions entail specialized infrastructure support for authentication, encryption and access control. Mobile applications executing over ad hoc wireless networks present designers with a rather distinct set of security requirements. A totally open setting and limited resources call for lightweight and highly decentralized security solutions. In this paper we propose an approach that relies on extending an existing coordination middleware for mobility (Lime). The need to continue to offer a very simple model of coordination that assures rapid software development led to limiting extensions solely to password protected tuple spaces and per tuple access control. Password distribution and security are relegated to the application realm. Host level security is ensured by the middleware design and relies on standard support provided by the Java system. Secure interactions among agents across hosts are accomplished by careful exploitation of the interceptor pattern and the use of standard encryption. The paper explains the design strategy used to add security support in Lime and its implications for the development of mobile applications over ad hoc networks.     

On aspectualizing component models

Server‐side component models such as Enterprise JavaBeans (EJB) add powerful abstractions to the bare ‘business objects’ layer in order to support a clean separation of server‐side application logic from other concerns such as distribution, security, transaction management and persistence. An improved separation of concerns is also the main goal of aspect‐oriented programming (AOP). This paper compares the two approaches and reasons about the possibility of substituting (parts of) component models using AOP mechanisms. We conclude that AOP is a promising approach to eliminate important shortcomings of the container‐based component approach. However, our analysis of concrete aspect‐oriented languages shows that current AOP technology is not yet mature enough to supersede component models. Copyright © 2003 John Wiley & Sons, Ltd.     

On the composability of consistency conditions

This paper presents a formal framework, which is based on the notion of a serialization set, that enables to compose a set of consistency conditions into a more restrictive one. To exemplify the utility of this framework, a list of very basic consistency conditions is identified, and it is shown that various compositions of the basic conditions yield some of the most commonly used consistency conditions, such as sequential consistency, causal memory, and Pipelined RAM. The paper also lists several applications that can benefit from even weaker semantics than Pipelined RAM that can be expressed as a composition of a small subset of the basic conditions.     

Weighted thin-plate spline image denoising

This note aims to present new denoising method based on thin-plate splines (TPS). The proposed approach is based on the general TPS denoising Berman [2], however, its unfavorable smoothing of edges and details is suppressed by introduction of a weighting approach applied locally. The performance of the method is shown and compared to the original TPS denoising.