A Frequency Domain Model to Predict the Estimation Accuracy of Packet Sampling

International audienceIn network measurement systems, packet sampling techniques are usually adopted to reduce the overall amount of data to collect and process. Being based on a subset of packets, they hence introduce estimation errors that have to be properly counteracted by a fine tuning of the sampling strategy and sophisticated inversion methods. This problem has been deeply investigated in the literature with particular attention to the statistical properties of packet sampling and the recovery of the original network measurements. Herein, we propose a novel approach to predict the energy of the sampling error on the real time traffic volume estimation, based on a spectral analysis in the frequency domain. We start by demonstrating that errors due to packet sampling can be modeled as an aliasing effect in the frequency domain. Then, we exploit this theoretical finding to derive closed-form expressions for the Signal-to-Noise Ratio (SNR), able to predict the distortion of traffic volume estimates over time. The accuracy of the proposed SNR metric is validated by means of real packet traces

A Communication Monitor for Wireless Sensor Networks Based on Software Defined Radio

Link quality estimation of reliability-crucial wireless sensor networks (WSNs) is often limited by the observability and testability of single-chip radio transceivers. The estimation is often based on collection of packer-level statistics, including packet reception rate, or vendor-specific registers, such as CC2420's Received Signal Strength Indicator (RSSI) and Link Quality Indicator (LQI). The speed or accuracy of such metrics limits the performance of reliability mechanisms built in wireless sensor networks. To improve link quality estimation in WSNs, we designed a powerful wireless communication monitor based on Software Defined Radio (SDR). We studied the relations between three implemented link quality metrics and packet reception rate under different channel conditions. Based on a comparison of the metrics' relative advantages, we proposed using a combination of them for fast and accurate estimation of a sensor network link

JamLab: Augmenting Sensornet Testbeds with Realistic and Controlled Interference Generation

Radio interference drastically affects the performance of sensor-net communications, leading to packet loss and reduced energy-efficiency. As an increasing number of wireless devices operates on the same ISM frequencies, there is a strong need for understanding and debugging the performance of existing sensornet protocols under interference. Doing so requires a low-cost flexible testbed infrastructure that allows the repeatable generation of a wide range of interference patterns. Unfortunately, to date, existing sensornet testbeds lack such capabilities, and do not permit to study easily the coexistence problems between devices sharing the same frequencies. This paper addresses the current lack of such an infrastructure by using off-the-shelf sensor motes to record and playback interference patterns as well as to generate customizable and repeat-able interference in real-time. We propose and develop JamLab: a low-cost infrastructure to augment existing sensornet testbeds with accurate interference generation while limiting the overhead to a simple upload of the appropriate software. We explain how we tackle the hardware limitations and get an accurate measurement and regeneration of interference, and we experimentally evaluate the accuracy of JamLab with respect to time, space, and intensity. We further use JamLab to characterize the impact of interference on sensornet MAC protocols

Applications of the wave packet method to resonant transmission and reflection gratings

Scattering of femtosecond laser pulses on resonant transmission and reflection gratings made of dispersive (Drude metals) and dielectric materials is studied by a time-domain numerical algorithm for Maxwell's theory of linear passive (dispersive and absorbing) media. The algorithm is based on the Hamiltonian formalism in the framework of which Maxwell's equations for passive media are shown to be equivalent to the first-order equation, $\partial \Psi/\partial t = {\cal H}\Psi$, where ${\cal H}$ is a linear differential operator (Hamiltonian) acting on a multi-dimensional vector $\Psi$ built of the electromagnetic inductions and auxiliary matter fields describing the medium response. The initial value problem is then solved by means of a modified time leapfrog method in combination with the Fourier pseudospectral method applied on a non-uniform grid that is constructed by a change of variables and designed to enhance the sampling efficiency near medium interfaces. The algorithm is shown to be highly accurate at relatively low computational costs. An excellent agreement with previous theoretical and experimental studies of the gratings is demonstrated by numerical simulations using our algorithm. In addition, our algorithm allows one to see real time dynamics of long leaving resonant excitations of electromagnetic fields in the gratings in the entire frequency range of the initial wide band wave packet as well as formation of the reflected and transmitted wave fronts.Comment: 23 pages; 8 figures in the png forma

Frequency-sweep examination for wave mode identification in multimodal ultrasonic guided wave signal

This article has been made available through the Brunel Open Access Publishing Fund.Ultrasonic guided waves can be used to assess and monitor long elements of a structure from a single position. The greatest challenges for any guided wave system are the plethora of wave modes arising from the geometry of the structural element which propagate with a range of frequency-dependent velocities and the interpretation of these combined signals reflected by discontinuities in the structural element. In this paper, a novel signal processing technique is presented using a combination of frequency-sweep measurement, sampling rate conversion, and Fourier transform. The technique is applied to synthesized and experimental data to identify different modes in complex ultrasonic guided wave signals. It is demonstrated throughout the paper that the technique also has the capability to derive the time of flight and group velocity dispersion curve of different wave modes in field inspections. © 2014 IEEE