This survey summarizes the state-of-the-art research on network coding, mainly focusing on its applications to computer networking. Network coding generalizes traditional store-and-forward routing techniques by allowing intermediate nodes in networks to encode several received packets into a single coded packet before forwarding. Network coding was proposed in 2000, and since then, it has been studied extensively in the field of computer networking. In this survey, we first summarize linear network coding and provide a taxonomy of network coding research, i.e., the network coding design problem and network coding applications. Moreover, the latter is subdivided into throughput/capacity enhancement, robustness enhancement, network tomography, and security. We then discuss the fundamental characteristics of network coding and diverse applications of network coding in details, following the above taxonomy.

An algorithm is formulated for reconstructing a dielectric cylinder with the use of the T-matrix and the singular value decomposition (SVD) and is discussed through numerical examples under noisy conditions. The algorithm consists of two stages. At the first stage the measured data of scattered waves is transformed into the T-matrix. At the second stage we reconstruct the cylinder from the T-matrix. The singular value decomposition is applied in order to separate the radiating and the nonradiating currents, and the radiating current is directly obtained from the T-matrix. The nonradiating current and the object are reconstructed by decreasing a residual error of the current in the least square approximation, where linear equations are solved repeatedly. Some techniques are used in order to reduce the calculation time and to reduce the effects of noise. Numerical examples show us that the presented approach is simple and numerically feasible, and enables us to reconstruct a large object in a short time.

This paper presents an IP performance management system having the triple frameworks of performance measurement, topology monitoring and data analysis. The system infers the causal location of the performance degradation with a network tomographic approach. Since the Internet is still highly prone to performance deterioration due to congestion, router failure, and so forth, not only detecting performance deterioration, but also monitoring topology and locating the performance-degraded segments in real-time is vital to ensure that Internet Service Providers can mitigate or prevent such performance deterioration. The system is implemented and evaluated through a real-world experiment and its considerable potential for practical network operations is demonstrated.

In network tomography, most work to date is based on exploiting probe packet level correlations to infer the link loss rates and delay distributions. Some other work focuses on identifying the congested links using uncorrelated end-to-end measurements and link prior probability of being congested. In their work, the prior probabilities are identified by the matrix inversion with a number of measurement snapshots, and the algorithm to find the congested links is heuristic and not optimal. In this letter, we present a new estimator for the prior probabilities that is computationally simple, being an explicit function of the measurement snapshots. With these prior probabilities, the identification of the congested link set is equivalent to finding the solution for a probability maximization problem. We propose a fast bottom-up approach named FBA to find the solution for this problem. The FBA optimizes the solution step by step from the bottom up. We prove that the solution by the FBA is optimal.

This paper shows that there is a fruitful world behind sampling theorems. For this purpose, the sampling problem is reformulated from a functional analytic standpoint, and is consequently revealed that the sampling problem is a kind of inverse problem. The sampling problem covers, for example, signal and image restoration including super resolution, image reconstruction from projections such as CT scanners in hospitals, and supervised learning such as learning in artificial neural networks. An optimal reconstruction operator is also given, providing the best approximation to an individual original signal without our knowing the original signal.

This letter proposes a novel method of large-scale IP traffic matrix estimation which is based on Partial Flow Measurement and Fratar Model (PFMFM). Firstly, we model OD flows as Fratar model and introduce the constrained relations between traffic matrix and link loads. By combining partial flow measurement, we can get a good prior value of network tomography. Then a good estimation of traffic matrix is attained with the modified network tomography method. Finally, we use the real data [8] from network Abilene to validate our method. In contrast to TomoGravity [1], the results show that our method improves remarkably and the estimation of traffic matrix is closer to real data, and especially when the flow is small and changes dramatically, the estimation is better.

In the acquisition of projection data of X-ray CT, logarithm operation is indispensable. But noise distribution is nonlinearly projected by the logarithm operation, and this deteriorates the precision of CT number. This influence becomes particularly remarkable when only a few photons are caught with a detector. It generates a strong streak artifact (SA) in a reconstructed image. Previously we have clarified the influence of the nonlinearity by statistical analysis and proposed a correction method for such nonlinearity. However, there is a problem that the compensation for clamp processing cannot be performed and that the suppression of SA is not enough in photon shortage state. In this paper, we propose a new technique for correcting the nonlinearity due to logarithm operation for noisy data by combining the previously presented method and an adaptive filtering method. The technique performs an adaptive filtering only when the number of captured photons is very few. Moreover we quantitatively evaluate the influence of noise on the reconstructed image in the proposed method by the experiment using numerical phantoms. The experimental results show that there is less influence on spatial resolution despite suppressing SA effectively and that CT number are hardly dependent on the number of the incident photons.

Electrical capacitance tomography (ECT) is used to obtain information about the distribution of a mixture of dielectric materials inside a vessel or pipe. ECT has several advantages over other reconstruction algorithms and has found many applications in the industrial fields. However, there are some difficulties with image reconstruction in ECT: The relationship between the permittivity distribution and measured capacitance is nonlinear. And inverse problem is ill-posed so that the inverse solution is sensitive to measurement error. To cope with these difficulties iterative image reconstruction algorithms have been developed. In general, the iterative reconstruction algorithms in ECT have comparatively good-quality in reconstructed images but result in intensive computational burden. This paper presents the iterative image reconstruction algorithm for ECT that can enhance the speed of image reconstruction without degradation in the quality of reconstructed image. The main contribution of the proposed algorithm is new weighting matrices, which are obtained by the interpolation of the grouped electrical field centre lines (EFCLs). Extensive simulation results have demonstrated that proposed algorithm provides improved reconstruction performance in terms of computational time and image quality.

Since congestion is very likely to happen in the Internet, locating congested areas (path segments) along a congested path is vital to appropriate actions by Internet Service Providers to mitigate or prevent network performance degradation. We propose a practical method to locate congested segments by actively measuring one-way end-to-end packet losses on appropriate paths from multiple origins to multiple destinations, using a network tomographic approach. Then we conduct a long-term experiment measuring packet losses on multiple paths over the Japanese commercial Internet. The experimental results indicate that the proposed method is able to precisely locate congested segments. Some findings on congestion over the Japan Internet are also given based on the experiment.

We implemented all-fiber delay line using linearly chirped fiber Bragg gratings (CFBG), which can be applicable for reflectometry or optical coherence tomography (OCT). Compared with the previously reported delay lines, the proposed fiber-based optical delay line has in principle novel advantages such as automatic dispersion cancellations without additional treatment and a gain in optical delay that is dependent on parameters of used CFBGs. Dispersion compensation in optical delay line (ODL), which is the indispensable problem in bulk optics based ODL, is demonstrated in fiber by using two identical but reversely ordered CFBGs. Amplified variable optical delay of around 2.5 mm can be obtained by applying small physical stretching of one of CFBGs in the proposed scheme. The operational principles of the all-fiber variable optical delay line, which are based on the distributed reflection characteristic of a CFBG employed, are described. Especially properties such as in-line automatic dispersion cancellation and amplified optical delay under strain are dealt. To demonstrate the properties of the proposed scheme, which is theoretical consequences under assumptions, an all-fiber optical delay line have been implemented using fiber optic components such as fiber couplers and fiber circulators. With the implanted ODL, the group delay and amplified optical delay length was measured with/without strain. The wavelength independent group delay measured within reflection bandwidth of the CFBG has proved the property of automatic dispersion cancellations in the proposed fiber delay line. Optical delay length of 2.5 mm was obtained when we apply small physical stretching to the CFBG by 100 µm and this is expressed by the amplification factor of 25. Amplification factor 25, which is less than theoretical value of 34 due to slipping of fiber in the fiber holder, shows that the proposed scheme can provide large optical delay with applying small physical stretching to the CFBG. We measure slide glass thickness to check the performance of the fiber delay line and the good agreement in measured and physical thickness of slide glass (1 mm thick) validates the potential of proposed delay line in the applications of optical reflectometry and OCT. We also discuss the problem and the solution to improve the performance.

The recent evolution on the network tomography have successfully provided principles and methodologies of inferring network-internal (local) characteristics solely from end-to-end measurements, which should be followed by deployment in practical use. In this paper, two kinds of user-oriented tools for inferring one-way packet losses based on the network tomography are proposed. They can infer one-way packet loss rates on paths or path segments from/to a user-host (a client) to/from a specified target host (an application server or a router) without any measurement on the target, and thus can find the congested area along the path between the client and an application server. One is a stand-alone tool running on the client, and the other is a client-server style tool running on both the client and a proxy measurement server distributed in the Internet. Prototypes of the tools have been developed and evaluated by experiments in the actual Internet environment, which shows that the tools can infer the loss rates within 1% errors in various network conditions.

In medical diagnosis, cone beam CT increases the dose absorbed by a patient. However, the radiographic noise (such as quantum noise) in a CT image increases when radiation exposure is reduced. In this paper, we propose a method to improve the CT image degraded by the quantum mottle based on 2-D wavelet transform modulus sum (WTMS). The noise and regular parts of an image can be observed by tracing the evolution of its 2-D WTMS across scales. Our experimental results show that most of the quantum mottle in the 2-D projections is removed by the proposed method and the edges preserved well. We investigate the relation between the number of X-ray photons and the quality of the denoised images. The result shows the possibility that a patient's dose can be reduced about 10% with the same visual quality by our method.

To improve the CT image degraded by radiographic noise (such as quantum mottle), we propose a method based on the wavelet transform modulus sum (WTMS). The noise and regular parts of a signal can be observed by tracing the evolution of its WTMS across scales. Our results show that most of the quantum mottle in the projections of Shepp-Logan phantom has been removed by the proposed method with the supposed cranium well preserved. The denoised CT images show good signal to noise ratio in the region of interest. We also have investigated the relation between the number of X-ray photons and the quality of images reconstructed from denoised projections. From experimental results, this method shows the possibility to reduce a patient's dose about 1/10 with the same visual quality.

Generalized Pulse Spectrum Technique (GPST) is a method to solve the inverse problems of wave-propagation and diffusion-dominated phenomena, and therefore has been popularly applied in image reconstruction of time-resolved diffuse optical tomography. With a standard GPST for simultaneous reconstruction of absorption and scattering coefficients, the products of the gradients of the Green's function and the photon-density flux, based on the photon-diffusion equation, are required to calculate the diffusion-related Jacobian matrix. The adversities are of two-folds: time-consuming and singular in the field near the source. The latter causes a severe insensitivity of the algorithm to the scattering changes deep inside tissue. To cope with the above difficulties, we propose in this paper a modified GPST algorithm that only involves the Green's function and the photon-density flux themselves in the scattering-related matrix. Our simulated and experimental reconstructions show that the modified algorithm can significantly improve the quality of scattering image and accelerate the reconstruction process, without an evident degradation in absorption image.

In Chirp-Pulse Microwave Computed Tomography (CP-MCT) the images are affected by the blur which is inherent to the measurement principle and is described by a space-variant Point Spread Function (PSF). In this paper we investigate the PSF of CP-MCT including the space dependence both experimentally and computationally. The experimental evaluation is performed by measuring the projections of a target consisting of a thin low-loss dielectric rod surrounded by a saline solution and placed at various positions in the measuring region. On the other hand, the theoretical evaluation is obtained by computing the projections of the same target via a numerical solution of Maxwell's equations. Since CP-MCT uses a chirp signal, the numerical evaluation is carried out by the use of a FD-TD method. The projections of the rod could be obtained by computing the field during the sweep time of the chirp signal for each position of the receiving antenna. Since this procedure is extremely time consuming, we compute the impulse response function of the system by exciting the transmitting antenna with a wide-band Gaussian pulse. Then the signal transmitted in CP-MCT is obtained by computing the convolution product in time domain of the input chirp pulse with the impulse response function of the system. We find a good agreement between measured and computed PSF. The rationality of the computed PSF is verified by three distinct ways and the usefulness of this function is shown by a remarkable effect in the restoration of CP-MCT images. Knowledge on the space-variant PSF will be utilized for more accurate image deblurring in CP-MCT.

This paper deals with a quantitative inversion algorithm for reconstructing the permittivity and conductivity profiles of bounded inhomogeneous buried objects from measured multifrequency and multiincidence backscattered field data. An Edge-Preserving regularization scheme is applied leading to a significant enhancement in the profiles reconstructions. The applications concern civil engineering and geophysics as well as mine detection and localization. The performance of the reconstructions are illustrated with different synthetic data.

This paper deals with two different quantitative inversion algorithms for reconstructing the complex permittivity profile of bounded inhomogeneous objects from measured scattered field data. The first algorithm involves an imaging method with single frequency excitation and multiincidence illumination and the second algorithm involves a method with synthetic pulse (multifrequency mode) excitation for objects surrounded by freespace or buried in stratified half-space media. Transmission or reflection imaging protocols are considered depending on aimed applications: microwave imaging in free-space from far-field data for target identification, microwave imaging from near-field data for nondestructive testing (NDT), microwave tomography of buried objects for mine detection and localization, civil engineering and geophysical applications. And Edge-Preserving regularization scheme leading to a significant enhancement in the image reconstructions is also proposed. The methods are illustrated with synthetic and experimental data.

The applicability of a boundary matching technique is presented for reconstructing the refractive-index profile of a circularly symmetric cylinder from the measurement of the scattered wave when the cylinder is illuminated by an H-polarized plane wave. The algorithm of reconstruction is based on an iterative procedure of matching the scattered wave calculated from a certain refractive-index distribution with the measured scattered-wave. The limits of reconstruction for strongly inhomogeneous lossless and lossy cylinders are numerically shown through computer simulations under noisy environment, and are compared with those in the E-wave case.

An attenuation correction method was proposed for laser-produced plasma emission computed tomography (ECT), which is based on a relation of the attenuation coefficient and the emission coefficient in plasma. Simulation results show that the reconstructed images are dramatically improved in comparison to the reconstructions without attenuation correction.

This paper describes fundamental system of borehole radars and its recent progress in Japan. Early development of borehole radars were carried out for detection of cracks in crystallized rock, however, the fields of applications are expanding to other various objects such as soil and sedimental rocks. Conventionally developed radar systems are not necessarily suitable for these applications and they must be modified. New technologies such as radar polarimetry and radar tomography were also introduced.