We propose an algorithm for the scattering analyses of gratings with various local defects based on the difference-field boundary-element method (DFBEM). In the algorithm, the defect in the grating is partitioned, and the DFBEM is sequentially applied for each defect section. We validate the proposed algorithm by demonstrating its flexibility for various defect topologies for a locally deformed grating.

The RO (Ring-Oscillator)-based sensor is one of easily-implementable variation sensors, but for decomposing the observed variability into multiple unique device-parameter variations, a large number of ROs with different structures and sensitivities to device-parameters is required. This paper proposes an area efficient device parameter estimation method with sensitivity-configurable ring oscillator (RO). This sensitivity-configurable RO has a number of configurations and the proposed method exploits this property for reducing sensor area and/or improving estimation accuracy. The proposed method selects multiple sets of sensitivity configurations, obtains multiple estimates and computes the average of them for accuracy improvement exploiting an averaging effect. Experimental results with a 32-nm predictive technology model show that the proposed averaging with multiple estimates can reduce the estimation error by 49% or reduce the sensor area by 75% while keeping the accuracy. Compared to previous work with iterative estimation, 23% accuracy improvement is achieved.

We propose a method of enhancing the performance of a cross-talk canceller for a four-speaker system with respect to sweet spot size and ringing effect. For the large sweet spot of a cross-talk canceller, the speaker layout needs to be symmetrical to the listener's position. In addition, a ringing effect of the cross-talk canceller is reduced when many speakers are located close to each other. Based on these properties, the proposed method first selects the two speakers in a four-speaker system that are most symmetrical to the target listener's position and then adds the remaining speakers between these two to the final selection. By operating only these selected speakers, the proposed method enlarges the sweet spot size and reduces the ringing effect. We conducted objective and subjective evaluations and verified that the proposed method improves the performance of the cross-talk canceller compared to the conventional method.

Ring aggregation networks are widely employed for metro access networks. A layer-2 ring with Ethernet Ring Protection is a popular topology for carrier services. Since frames are forwarded along ring nodes, a fairness scheme is required to achieve throughput fairness. Although per-node fairness algorithms have been developed for the Resilient Packet Ring, the per-node fairness is insufficient if there is bias in a flow distribution. To achieve per-flow fairness, N Rate N+1 Color Marking (NRN+1CM) was proposed. However, NRN+1CM can achieve fairness in case there are sufficient numbers of available bits on a frame header. It cannot be employed if the frame header cannot be overwritten. Therefore, the application range of NRN+1CM is limited. This paper proposes a Signaling based Discard with Flags (SDF) scheme for per-flow fairness. The objective of SDF is to eliminate the drawback of NRN+1CM. The key idea is to attach a flag to frames according to the input rate and to discard them selectively based on the flags and a dropping threshold. The flag is removed before the frame is transmitted to another node. The dropping threshold is cyclically updated by signaling between ring nodes and a master node. The SDF performance was confirmed by employing a theoretical analysis and computer simulations. The performance of SDF was comparable to that of NRN+1CM. It was verified that SDF can achieve per-flow throughput fairness without using a frame header in ring aggregation networks.

A novel dynamic element matching (DEM) method, called binary-tree random DEM (BTR-DEM), is presented for a Nyquist-rate current-steering digital-to-analog converter (DAC). By increasing or decreasing the number of unit current sources randomly at the same time, the BTR-DEM encoding reduces switch transition glitches. A 5-bit current-steering DAC with the BTR-DEM technique is implemented in a 65-nm CMOS technology. The measured spurious free dynamic range (SFDR) attains 42 dB for a sample rate of 100 MHz and shows little dependence on signal frequency.

The harmonious coloring of an undirected simple graph is a vertex coloring such that adjacent vertices are assigned different colors and each pair of colors appears together on at most one edge. The harmonious chromatic number of a graph is the least number of colors used in such a coloring. The harmonious chromatic number of a path is known, whereas the problem to find the harmonious chromatic number is NP-hard even for trees with pathwidth at most 2. Hence, we consider the harmonious coloring of trees with pathwidth 1, which are also known as caterpillars. This paper shows the harmonious chromatic number of a caterpillar with at most one vertex of degree more than 2. We also show the upper bound of the harmonious chromatic number of a 3-regular caterpillar.

A threshold secret sharing scheme can realize reliable delivery of important content using redundant routes through a network. Furthermore, multicast delivery of threshold secret shared content can achieve efficient resource utilization thanks to the application of multicast and network coding techniques to multiple pieces of the content. Nevertheless, a tradeoff exists between reliability and efficiency if multicast content delivery uses network coding. This paper proposes a flexible multicast delivery scheme for threshold secret shared content that can control the tradeoff between reliability and efficiency. The proposed scheme classifies all the pieces obtained from the original content into multiple groups, and each group is subjected to network coding independently. An optimization procedure is proposed for the multicast delivery scheme, which involves two different heuristic delivery route computation methods applicable to large-scale networks. Evaluation results show that the optimized multicast delivery scheme adopting an appropriate grouping method and classifying the pieces into a suitable number of groups can minimize the required link bandwidth while satisfying a specified content loss probability requirement.

Application prefetchers improve application launch performance on HDDs through either I/O reordering or I/O interleaving, but there has been no proposal to combine the two techniques. We present a new algorithm to combine both approaches, and demonstrate that it reduces cold start launch time by 50%.

Microwave ultra-wideband (UWB) radar systems are advantageous for their high-range resolution and ability to penetrate dielectric objects. Internal imaging of dielectric objects by UWB radar is a promising nondestructive method of testing aging roads and bridges and a noninvasive technique for human body examination. For these applications, we have already developed an accurate internal imaging approach based on the range points migration (RPM) method, combined with a method that efficiently estimates the dielectric constant. Although this approach accurately extracts the internal boundary, it is applicable only to highly conductive targets immersed in homogeneous dielectric media. It is not suitable for multi-layered dielectric structures such as human tissues or concrete objects. To remedy this limitation, we here propose a novel dielectric constant and boundary extraction method for double-layered materials. This new approach, which simply extends the Envelope method to boundary extraction of the inner layer, is evaluated in finite difference time domain (FDTD)-based simulations and laboratory experiments, assuming a double-layered concrete cylinder. These tests demonstrate that our proposed method accurately and simultaneously estimates the dielectric constants of both media and the layer boundaries.

Conventional localization techniques such as triangulation and multilateration are not reliable in non-line-of-sight (NLOS) environments such as dense urban areas. Although fingerprint-based localization techniques have been proposed to solve this problem, we may face difficulties because we do not know the parameters of the illegal radio when creating the fingerprint database. This paper proposes a novel technique to localize illegal radios in an urban environment by interpolating the channel impulse responses stored as fingerprints in a database. The proposed interpolation technique consists of interpolation in the bandwidth (delay), frequency and spatial domains. A localization algorithm that minimizes the squared error criterion is employed in this paper, and the proposed technique is evaluated through Monte Carlo simulations using location fingerprints obtained from ray-tracing simulations. Results show that utilizing an interpolated fingerprint database is advantageous in such scenarios.

The role of an optical low-pass filter (OLPF) in a digital still camera is to remove the high spatial frequencies that cause aliasing, thereby enhancing the image quality. However, this also causes some loss of detail. Yet, when an image is captured without the OLPF, moiré generally appears in the high spatial frequency region of the image. Accordingly, this paper presents a moiré reduction method that allows omission of the OLPF. Since most digital still cameras use a CCD or a CMOS with a Bayer pattern, moiré patterns and color artifacts are simultaneously induced by aliasing at high spatial frequencies. Therefore, in this study, moiré reduction is performed in both the luminance channel to remove the moiré patterns and the color channel to reduce color smearing. To detect the moiré patterns, the spatial frequency response (SFR) of the camera is first analyzed. The moiré regions are identified using patterns related to the SFR of the camera and then analyzed in the frequency domain. The moiré patterns are reduced by removing their frequency components, represented by the inflection point between the high-frequency and DC components in the moiré region. To reduce the color smearing, color changing regions are detected using the color variation ratios for the RGB channels and then corrected by multiplying with the average surrounding colors. Experiments confirm that the proposed method is able to reduce the moiré in both the luminance and color channels, while also preserving the detail.

Recently in the mobile graphic industry, ultra-realistic visual qualities with 60fps and limited power budget for GPU have been required. For graphics-heavy applications that run at 30 fps, we easily observed very noticeable flickering artifacts. Further, the workload imposed by high resolutions at high frame rates directly decreases the battery life. Unlike the recent frame rate up sampling algorithms which remedy the flickering but cause inevitable significant overheads to reconstruct intermediate frames, we propose a dynamic rendering quality scaling (DRQS) that includes dynamic rendering based on resolution changes and quality scaling to increase the frame rate with negligible overhead using a transform matrix. Further DRQS reduces the workload up to 32% without human visual-perceptual changes for graphics-light applications.

This study improves the compression efficiency of Lee's colorization-based coding framework by introducing a novel colorization matrix construction and an adaptive color conversion. Colorization-based coding methods reconstruct color components in the decoder by colorization, which adds color to a base component (a grayscale image) using scant color information. The colorization process can be expressed as a linear combination of a few column vectors of a colorization matrix. Thus it is important for colorization-based coding to make a colorization matrix whose column vectors effectively approximate color components. To make a colorization matrix, Lee's colorization-based coding framework first obtains a base and color components by RGB-YCbCr color conversion, and then performs a segmentation method on the base component. Finally, the entries of a colorization matrix are created using the segmentation results. To improve compression efficiency on this framework, we construct a colorization matrix based on a correlation of base-color components. Furthermore, we embed an edge-preserving smoothing filtering process into the colorization matrix to reduce artifacts. To achieve more improvement, our method uses adaptive color conversion instead of RGB-YCbCr color conversion. Our proposed color conversion maximizes the sum of the local variance of a base component, which resulted in increment of the difference of intensities at region boundaries. Since segmentation methods partition images based on the difference, our adaptive color conversion leads to better segmentation results. Experiments showed that our method has higher compression efficiency compared with the conventional method.

Mobile virtual network operators (MVNOs) are mobile operators without their own infrastructure or government issued spectrum licenses. They purchase spectrum resources from primary mobile network operators (MNOs) to provide communication services under their own brands. MVNOs are expected to play an important role in mobile network markets, as this will increase the competition in retail markets and help to meet the demand of niche markets. However, with the rapidly increasing demand of mobile data traffic, efficient utilization of the limited spectrum resources owned by MVNOs has become an important issue. We propose here a resource sharing mechanism between MVNOs against the background of network functions virtualization (NFV). The proposed mechanism enables MVNOs to improve their quality of service (QoS) by sharing spectrum resources with each other. A nash bargaining solution based decision strategy is also devised to ensure the fairness of resource sharing. Extensive numerical evaluation results validate the effectiveness of the proposed models and mechanisms.

Point spread function (PSF) estimation plays a paramount role in image deblurring processing, and traditionally it is solved by parameter estimation of a certain preassumed PSF shape model. In real life, the PSF shape is generally arbitrary and complicated, and thus it is assumed in this manuscript that a PSF may be decomposed as a weighted sum of a certain number of Gaussian kernels, with weight coefficients estimated in an alternating manner, and an l1 norm-based total variation (TVl1) algorithm is adopted to recover the latent image. Experiments show that the proposed method can achieve satisfactory performance on synthetic and realistic blurred images.

The hop-limited adaptive routing (HLAR) mechanism and its enhancement (EHLAR), both tailored for the packet-switched non-geostationary (NGEO) satellite networks, are proposed and evaluated. The proposed routing mechanisms exploit both the predictable topology and inherent multi-path property of the NGEO satellite networks to adaptively distribute the traffic via all feasible neighboring satellites. Specifically, both mechanisms assume that a satellite can send the packets to their destinations via any feasible neighboring satellites, thus the link via the neighboring satellite to the destination satellite is assigned a probability that is proportional to the effective transmission to the destination satellites of the link. The satellite adjusts the link probability based on the packet sending information observed locally for the HLAR mechanism or exchanged between neighboring satellites for the EHLAR mechanism. Besides, the path of the packets are bounded by the maximum hop number, thus avoiding the unnecessary over-detoured packets in the satellite networks. The simulation results corroborate the improved performance of the proposed mechanisms compared with the existing in the literature.

This paper proposes fast repairing methods that uses hierarchical software defined network controllers for recovering from massive failure in a large-scale IP over a wavelength-division multiplexing network. The network consists of multiple domains, and slave controllers are deployed in each domain. While each slave controller configures transport paths in its domain, the master controller manages end-to-end paths, which are established across multiple domains. For fast repair of intra-domain paths by the slave controllers, we define the optimization problem of path configuration order and propose a heuristic method, which minimizes the repair time to move from a disrupted state to a suboptimal state. For fast repair of end-to-end path through multiple domains, we also propose a network abstraction method, which efficiently manages the entire network. Evaluation results suggest that fast repair within a few minutes can be achieved by applying the proposed methods to the repairing scenario, where multiple links and nodes fail, in a 10,000-node network.

Anchor graph hashing (AGH) is a promising hashing method for nearest neighbor (NN) search. AGH realizes efficient search by generating and utilizing a small number of points that are called anchors. In this paper, we propose a method for improving AGH, which considers data distribution in a similarity space and selects suitable anchors by performing principal component analysis (PCA) in the similarity space.

Although the use of software-defined networking (SDN) enables routes of packets to be controlled with finer granularity (down to the individual flow level) by using traffic engineering (TE) and thereby enables better balancing of the link loads, the corresponding increase in the number of states that need to be managed at routers and controller is problematic in large-scale networks. Aggregating flows into macro flows and assigning routes by macro flow should be an effective approach to solving this problem. However, when macro flows are constructed as TE targets, variations of traffic rates in each macro flow should be minimized to improve route stability. We propose two methods for generating macro flows: one is based on a greedy algorithm that minimizes the variation in rates, and the other clusters micro flows with similar traffic variation patterns into groups and optimizes the traffic ratio of extracted from each cluster to aggregate into each macro flow. Evaluation using traffic demand matrixes for 48 hours of Internet2 traffic demonstrated that the proposed methods can reduce the number of TE targets to about 1/50 ∼ 1/400 without degrading the link-load balancing effect of TE.

We present a power-saving method for large-scale storage systems of cloud data sharing services, particularly those providing media (video and photograph) sharing services. The idea behind our method is to periodically rearrange stored data in a disk array, so that the workload is skewed toward a small subset of disks, while other disks can be sent to standby mode. This idea is borrowed from the Popular Data Concentration (PDC) technique, but to avoid an increase in response time caused by the accesses to disks in standby mode, we introduce a function that predicts future access frequencies of the uploaded files. This function uses the correlation of potential future accesses with the combination of elapsed time after upload and the total number of accesses in the past. We obtain this function in statistical analysis of the real access patterns of 50,000 randomly selected publicly available photographs on Flickr over 7,000 hours (around 10 months). Moreover, to adapt to a constant massive influx of data, we propose a mechanism that effectively packs the continuously uploaded data into the disk array in a storage system based on the PDC. To evaluate the effectiveness of our method, we measured the performance in simulations and a prototype implementation. We observed that our method consumed 12.2% less energy than the static configuration (in which all disks are in active mode). At the same time, our method maintained a preferred response time, with 0.23% of the total accesses involving disks in standby mode.