Unveiling the underlying relationships over a network for monitoring purposes

Nowadays traffic monitoring and analysis tools provide poor information about traffic volume without giving any clear view of what the hidden rules and relationships that govern these flows are. Since the majority of flows is generated by services (web browsing, email, p2p) and most of these applications are dependent on many network assets (servers and databases) we should discover the underlying relationships of every application. We present a technique that discovers the hidden relationships among components of a network that consist of parts of specific applications. From time information and flow attributes, such as IP addresses and service ports, our method using a novel hybrid genetic algorithm produces a small set of fuzzy rules that can reveal the underlying relationships over a network without any guidance. These dependencies build a service graph which can become a useful tool for fault localization, monitoring service performance, designing changes and anomaly detection. Copyright © 2009 John Wiley & Sons, Ltd.     

Empirical estimates of the direct rebound effect: A review

Improvements in energy efficiency make energy services cheaper, and therefore encourage increased consumption of those services. This so-called direct rebound effect offsets the energy savings that may otherwise be achieved. This paper provides an overview of the theoretical and methodological issues relevant to estimating the direct rebound effect and summarises the empirical estimates that are currently available. The paper focuses entirely on household energy services, since this is where most of the evidence lies and points to a number of potential sources of bias that may lead the effect to be overestimated. For household energy services in the OECD, the paper concludes that the direct rebound effect should generally be less than 30%.     

Noise Figure of Silicon Raman Amplifiers

The noise figure of silicon Raman amplifiers in the presence of nonlinear losses is calculated. The impact of two-photon absorption (TPA) and free-carrier scattering on the noise figure is quantified using the quantum formulation of the Langevin approach. It is found that TPA-induced free-carrier loss degrades the noise figure by an amount that depends on the carrier lifetime. For example, in a 1-cm-long waveguide pumped at 200 MW/cm², the noise figure is 5.2 dB for a lifetime of tau = 1.6 ns and is reduced to 3.7 dB for tau = 0.1 ns. The reduction in the noise figure along with a concomitant increase in Raman gain from 2 to 8 dB suggests that lifetimes on the order of 0.1 ns or less are needed to create a useful silicon Raman amplifier that operates in the continuous-wave mode. It is also shown that in devices that use a p-n junction for carrier sweep-out, the screening of the junction field by generated free carriers results in a sharp increase in the noise figure at high-pump intensities. These results apply to operation in the near-infrared communication wavelengths. For mid-infrared wavelengths above the two photon absorption band-edge (2.3 nm), the absence of TPA and pump-induced free-carrier absorption ensures that the amplifier has a low-noise figure.     

New Magnetic Field Sensor Based on Combined Flux-Gate/Hall-Effect Arrangement

A novel planar magnetic field sensor is presented that is based on a combined flux-gate/Hall-effect arrangement capable of measuring the three components of a three-dimensional quasi-static magnetic field. The proposed device involves a thin, isotropic, circular magnetic core, the magnetization of which is driven to saturation by means of a rotating excitation-field, produced by four printed planar coils. That way, the core magnetization rotates, without Barkhausen jumps inducing a flux-density change that is sensed by a Hall device positioned at the edge of the core. The presented sensor consists of a discrete Hall device, electronic modulation-demodulation circuitry and a circular amorphous core packaged on a printed circuit board (PCB), constructed as a proof of concept for the proposed magnetic field measuring method.     

Assessing the determinants of local acceptability of wind-farm investment: A choice experiment in the Greek Aegean Islands

This paper aims at analysing the factors, which motivate communities to resist the installation of wind farms in their vicinity. To this end, the choice experiment methodology was employed in communities in two Greek Aegean Islands to assess the determinants of preferences towards different wind-farm projects. Unlike other studies, the willingness to accept welfare measure was adopted. The results of our analysis show that the conservation status of the area where the wind farms are to be installed, along with the governance characteristics of the planning procedure are the most important determinants of local community welfare in relation to wind farms. In contrast to other studies, we find that the physical attributes of wind farms appear to be of less relative importance from a local community welfare point of view. Implications for the EU's future energy policy are drawn.     

On a new principle of a smart multisensor based on magnetic effects

In this paper, a new principle of a smart sensor is proposed, based on three different magnetic effects or operational modes, using the same sensor topology, which consists of a magnetic wire as sensing core, two coils as excitation or search means, and two electric contacts at the ends of the magnetic wire. The magnetic effects currently involved are magnetostriction, magneto-impedance and re-entrant flux reversal. Operating the sensor in these three different modes separately and sequentially, one can obtain the response of the sensor related to three different physical quantities, such as stress, temperature, and field. This paper refers to the first experimental results based on this principle, thus initiating the research work in this field. It has been experimentally observed that the total output of the sensor in each one of the three different modes is equal to the product of each corresponding physical quantity function concerned, provided that a given threshold of the ambient field and preloaded stress is used to bias the sensing element. Therefore, the three unknown parameters of stress, temperature, and field can be determined from a 3/spl times/3 matrix equation. Other magnetic effects may also be involved. Furthermore, other physical quantities may also be determined, such as position, pressure, load, etc.     

Noise sources in miniature fluxgate sensors Part I: theoretical treatment

A mathematical model for miniature fluxgate magnetometers is presented in the first part of this work. It is based on certain well-defined and easy-measurable parameters of the hysteresis loop exhibited by the fluxgate magnetic core, i.e., the coercive force and the field intensities at which the flux-reversal starts and saturates. Two signal extraction techniques are modeled, the classical second-order harmonic one, and the current sampling one. For both cases, analytical expressions (in time and frequency domains) are derived for the magnetometer transfer function (voltage vs field) and the influence of the aforementioned hysteresis loop parameters on the magnetometer response. Consequently the signal-to-noise ratio (SNR) in the ELF (Extremely Low Frequency) range and the effective magnetometer bandwidth are calculated for both cases. The SNR is a function of the variance of the aforementioned hysteresis loop parameters. Several noise-sources of different origin have been found to influence this variance, namely: (a) the magnetic (Barkhausen) noise, (b) the noise superimposed to the excitation waveform, (c) the noise generated due to electromagnetic-interference, and (d) the noise generated due to mechanical vibration of fluxgate cores. The extend, up to which the power of these noise-sources boost the variance of the aforementioned hysteresis loop parameters, is a function of certain fluxgate core characteristics, namely: (a) the saturation magnetization, (b) the coercive field, (c) the flux-reversal duration, (d) the dependence of flux-reversal duration on the excitation field slope (slew rate), (e) the core cross-section, and (f) the core frequency response (magnetic damping and magnetic viscosity). Finally, the conditions are investigated so that the current-sampling technique exhibits better SNR compared to the classical second-order-harmonic one. In the second part of this work the theory presented here is applied to explain the noise performance of miniature fluxgates employing amorphous wire cores.     

Raman-based silicon photonics

This paper reviews recent progress in a new branch of silicon photonics that exploits Raman scattering as a practical and elegant approach for realizing active photonic devices in pure silicon. The large Raman gain in the material, enhanced by the tight optical confinement in Si/SiO2 heterostructures, has enabled the demonstration of the first optical amplifiers and lasers in silicon. Wavelength conversion, between the technologically important wavelength bands of 1300 and 1500 nm, has also been demonstrated through Raman four wave mixing. Since carrier generation through two photon absorption is omnipresent in semiconductors, carrier lifetime is the single most important parameter affecting the performance of silicon Raman devices. A desired reduction in lifetime is attained by reducing the lateral dimensions of the optical waveguide, and by actively removing the carriers with a reverse biased diode. An integrated diode also offers the ability to electrically modulate the optical gain, a unique property not available in fiber Raman devices. Germanium-silicon alloys and superlattices offer the possibility of engineering the otherwise rigid spectrum of Raman in silicon.     

FaRNet: Fast recognition of high-dimensional patterns from big network traffic data

Extracting knowledge from big network traffic data is a matter of foremost importance for multiple purposes including trend analysis, network troubleshooting, capacity planning, network forensics, and traffic classification. An extremely useful approach to profile traffic is to extract and display to a network administrator the multi-dimensional hierarchical heavy hitters (HHHs) of a dataset. However, existing schemes for computing HHHs have several limitations: (1) they require significant computational resources; (2) they do not scale to high dimensional data; and (3) they are not easily extensible. In this paper, we introduce a fundamentally new approach for extracting HHHs based on generalized frequent item-set mining (FIM), which allows to process traffic data much more efficiently and scales to much higher dimensional data than present schemes. Based on generalized FIM, we build and thoroughly evaluate a traffic profiling system we call FaRNet. Our comparison with AutoFocus, which is the most related tool of similar nature, shows that FaRNet is up to three orders of magnitude faster. Finally, we describe experiences on how generalized FIM is useful in practice after using FaRNet operationally for several months in the NOC of GÉANT, the European backbone network.