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This paper presents Pando, a completely contention-free data dissemination protocol for wireless sensor networks. Pando encodes data by Fountain codes and disseminates the rateless stream of encoded packets along the fast and parallel pipelines built on constructive interference and channel diversity. Since every encoded packet contains innovative information to the original data object, Pando avoids duplicate retransmissions and fully exploits the wireless broadcast effect in data dissemination. To transform Pando into a practical system, we devise several techniques, including the integration of Fountain coding with the timing-critical operations of constructive interference and pipelining, a silence-based feedback scheme for the one-way pipelined dissemination, and packet-level adaptation of network density and channel diversity. Based on these techniques, Pando can accomplish data dissemination entirely over the fast and parallel pipelines. We implement Pando in Contiki and for TelosB motes. We evaluate Pando with various settings on two large-scale open test beds, Indriya and Flocklab. Our experimental results show that Pando can provide 100% reliability and reduce the dissemination time of state of the art by $3.5\times $ . [ABSTRACT FROM AUTHOR]

Screen-camera links for Visible Light Communication (VLC) are diverse, as the link quality varies according to many factors, such as ambient light and camera's performance. This paper presents SoftLight, a channel coding approach that considers the unique channel characteristics of VLC links and automatically adapts the transmission data rate to the link qualities of various scenarios. SoftLight incorporates two new ideas: (1) an expanded color modulation interface that provides soft hint about its confidence in each demodulated bit and establishes a bit-level VLC erasure channel, and (2) a rateless coding scheme that achieves bit-level rateless transmissions with low computation complexity and tolerates the false positive of bits provided by the soft hint enabled erasure channel. SoftLight is orthogonal to the visual coding schemes and can be applied atop any barcode layouts. We implement SoftLight on Android smartphones and evaluate its performance under a variety of environments. The experiment results show that SoftLight can correctly transmit a 22-KByte photo between two smartphones within 0.6 second and improves the average goodput of the state-of-the-art screen-camera VLC solution by 2.2$\times$ . [ABSTRACT FROM AUTHOR]

This paper presents a distanceless networking approach for wireless sensor networks sparsely deployed in large areas. By leveraging rateless codes, we provide distanceless transmission to expand the communication range of sensor motes and fully exploit network diversity. We address a variety of practical challenges to accommodate rateless coding on resource-constrained sensor motes and devise a communication protocol to efficiently coordinate the distanceless link transmissions. We propose a new metric (expected distanceless transmission time) for routing selection and further adapt the distanceless transmissions to low duty-cycled sensor networks. We implement the proposed scheme in TinyOS on the TinyNode platform and deploy the sensor network in a real-world project, in which 12 wind measurement sensors are installed around a large urban reservoir of 2.5\,\times\,3.0 km^2 to monitor the field wind distribution. Extensive experiments show that our proposed scheme significantly outperforms the state-of-the-art approaches for data collection in sparse sensor networks. [ABSTRACT FROM PUBLISHER]

In order to derive reliable propagation models for future terahertz indoor pico-cellular communication systems, accurate reflectivity data of building materials is necessary. Here we present reflection terahertz time domain spectroscopy (THz-TDS) measurements and matching transfer matrix simulations of the frequency dependent reflection coefficient of multi layer building materials in the frequency range from 100 to 500 GHz for a set of angles, both in TEand TM-polarization. Two prominent stratifled structures, a double pane window and white paint on plaster are investigated as they usually account for large areas in indoor environments. Communication systems located above 100 GHz are expected to be strongly affected by the variations of the reflectivity over the frequency and incident angle of such stratified materials as they will rely both on line of sight (LOS) and non line of sight (NLOS) propagation. We discuss this impact on the power distribution in a sample scenario employing the ray-tracing method. [ABSTRACT FROM AUTHOR]

Modeling propagation channels for future pico-cellular indoor THz communication systems requires the knowledge of the reflective properties of building materials. The reflectivity of smooth, optically thick materials can be modeled with Fresnel equations. In case of materials with a rough surface, diffuse scattering reduces the power reflected in the specular direction. Kirchhoff scattering theory can be employed to derive modified Fresnel equations which account for these losses by introducing a Rayleigh roughness factor calculated from the measured surface height distribution of the sample under observation. Using the resulting, analytically derived reflection coefficient based on material parameter and surface measurements in propagation models enables the simulation of arbitrary configurations. We present a set of calculated and measured reflection coefficients for a selection of common indoor building materials which are in good agreement, thus verifying our modeling approach. Furthermore, we illustrate by rayracing simulations the effect of wall and ceiling roughness on propagation in future indoor scenarios. Both, absolute power levels and propagation patterns are shown to be strongly influenced by scattering. In some cases, reflected transmissions with longer propagation paths can be more efficient than the shorter ones in terms of incurred losses. [ABSTRACT FROM AUTHOR]

We present a new computational method for reconstructing a vector velocity field from scattered, pulsed-wave ultrasound Doppler data. The main difficulty is that the Doppler measurements are incomplete, for they do only capture the velocity component along the beam direction. We thus propose to combine measurements from different beam directions. However, this is not yet sufficient to make the problem well posed because 1) the angle between the directions is typically small and 2) the data is noisy and nonuniformly sampled. We propose to solve this reconstruction problem in the continuous domain using regularization. The reconstruction is formulated as the minimizer of a cost that is a weighted sum of two terms: 1) the sum of squared difference between the Doppler data and the projected velocities 2) a quadratic regularization functional that imposes some smoothness on the velocity field. We express our solution for this minimization problem in a B-spline basis, obtaining a sparse system of equations that can be solved efficiently. Using synthetic phantom data, we demonstrate the significance of tuning the regularization according to the a priori knowledge about the physical property of the motion. Next, we validate our method using real phantom data for which the ground truth is known. We then present reconstruction results obtained from clinical data that originate from 1) blood flow in carotid bifurcation and 2) cardiac wall motion. [ABSTRACT FROM AUTHOR]

Wavelet-based methods have become most popular for the compression of two-dimensional medical images and sequences. The standard implementations consider data sizes that are powers of two. There is also a large body of literature treating issues such as the choice of the "optimal" wavelets and the performance comparison of competing algorithms. With the advent of telemedicine, there is a strong incentive to extend these techniques to higher dimensional data such as dynamic three-dimensional (3-D) echocardiography [four-dimensional (4-D) datasets]. One of the practical difficulties is that the size of this data is often not a multiple of a power of two, which can lead to increased computational complexity and impaired compression power. Our contribution in this paper is to present a genuine 4-D extension of the well-known zerotree algorithm for arbitrarily sized data. The key component of our method is a one-dimensional wavelet algorithm that can handle arbitrarily sized input signals. The method uses a pair of symmetric/antisymmetric wavelets (10/6) together with some appropriate midpoint symmetry boundary conditions that reduce border artifacts. The zerotree structure is also adapted so that it can accommodate noneven data splitting. We have applied our method to the compression of real 3-D dynamic sequences from clinical cardiac ultrasound examinations. Our new algorithm compares very favorably with other more ad hoc adaptations (image extension and tiling) of the standard powers-of-two methods, in terms of both compression performance and computational cost. It is vastly superior to slice-by-slice wavelet encoding. This was seen not only in numerical image quality parameters but also in expert ratings, where significant improvement using the new approach could be documented. Our validation experiments show that one can safely compress 4-D data sets at ratios of 128:1 without compromising the diagnostic value of the images. We also display some more extreme... [ABSTRACT FROM AUTHOR]