Live migration plays an important role on improving efficiency of cloud data centers by enabling dynamically replacing virtual machines (VMs) without disrupting services running on them. Although many studies have proposed acceleration mechanisms of live migration, IO-intensive VMs still suffer from long total migration time due to a large amount of page cache. Existing studies for this problem either force the guest OS to delete the page cache before a migration, or they do not consider dynamic characteristics of cloud data centers. We propose a parallel and adaptive transfer of page cache for migrating IO-intensive VMs which (1) does not delete the page cache and is still fast by utilizing the storage area network of a data center, and (2) achieves the shortest total migration time without tuning hand-crafted parameters. Experiments showed that our method reduces total migration time of IO-intensive VMs up to 33.9%.

The key escrow problem and high computational cost are the two major problems that hinder the wider adoption of hierarchical identity-based signature (HIBS) scheme. HIBS schemes with either escrow-free (EF) or online/offline (OO) model have been proved secure in our previous work. However, there is no much EF or OO scheme that has been evaluated experimentally. In this letter, several EF/OO HIBS schemes are considered. We study the algorithmic complexity of the schemes both theoretically and experimentally. Scheme performance and practicability of EF and OO models are discussed.

Power analysis for IoT devices is strongly required to protect attacks from malicious attackers. It is also very important to reduce power consumption itself of IoT devices. In this paper, we propose a highly-adaptable and small-sized in-field power analyzer for low-power IoT devices. The proposed power analyzer has the following advantages: (A) The proposed power analyzer realizes signal-averaging noise reduction with synchronization signal lines and thus it can reduce wide frequency range of noises; (B) The proposed power analyzer partitions a long-term power analysis process into several analysis segments and measures voltages and currents of each analysis segment by using small amount of data memories. By combining these analysis segments, we can obtain long-term analysis results; (C) The proposed power analyzer has two amplifiers that amplify current signals adaptively depending on their magnitude. Hence maximum readable current can be increased with keeping minimum readable current small enough. Since all of (A), (B) and (C) do not require complicated mechanisms nor circuits, the proposed power analyzer is implemented on just a 2.5cm×3.3cm board, which is the smallest size among the other existing power analyzers for IoT devices. We have measured power and energy consumption of the AES encryption process on the IoT device and demonstrated that the proposed power analyzer has only up to 1.17% measurement errors compared to a high-precision oscilloscope.

We investigate the coding scheme and error probability in information transmission over continuous-time additive Gaussian noise channels with feedback. As is known, the error probability can be substantially reduced by using feedback, namely, under the average power constraint, the error probability may decrease more rapidly than the exponential of any order. Recently Gallager and Nakibolu proposed, for discrete-time additive white Gaussian noise channels, a feedback coding scheme such that the resulting error probability Pe(N) at time N decreases with an exponential order αN which is linearly increasing with N. The multiple-exponential decay of the error probability has been studied mostly for white Gaussian channels, so far. In this paper, we treat continuous-time Gaussian channels, where the Gaussian noise processes are not necessarily white nor stationary. The aim is to prove a stronger result on the multiple-exponential decay of the error probability. More precisely, for any positive constant α, there exists a feedback coding scheme such that the resulting error probability Pe(T) at time T decreases more rapidly than the exponential of order αT as T→∞.

Many studies have applied the three-dimensional discrete wavelet transform (3D DWT) to video coding. It is known that corruptions of the lowest frequency sub-band (LL) coefficients of 3D DWT severely affect the visual quality of video. Recently, we proposed an error resilient 3D DWT video coding method (the conventional method) that employs dispersive grouping and an error concealment (EC). The EC scheme of our conventional method adopts a replacement technique of the lost LL coefficients. In this paper, we propose a new 3D DWT video transmission method in order to enhance error resilience. The proposed method adopts an error correction scheme using invertible codes to protect LL coefficients. We use half-rate Reed-Solomon (RS) codes as invertible codes. Additionally, to improve performance by using the effect of interleave, we adopt a new configuration scheme at the RS encoding stage. The evaluation by computer simulation compares the performance of the proposed method with that of other EC methods, and indicates the advantage of the proposed method.

Average coding rate of a multi-shot Tunstall code, which is a variation of variable-to-fixed length (VF) lossless source codes, for stationary memoryless sources is investigated. A multi-shot VF code parses a given source sequence to variable-length blocks and encodes them to fixed-length codewords. If we consider the situation that the parsing count is fixed, overall multi-shot VF code can be treated as a one-shot VF code. For this setting of Tunstall code, the compression performance is evaluated using two criterions. The first one is the average coding rate which is defined as the codeword length divided by the average block length. The second one is the expectation of the pointwise coding rate. It is proved that both of the above average coding rate converge to the entropy of a stationary memoryless source under the assumption that the geometric mean of the leaf counts of the multi-shot Tunstall parsing trees goes to infinity.

In this paper, we propose a novel placement algorithm for mixed-grained reconfigurable architectures (MGRAs). MGRA consists of coarse-grained and fine-grained clusters, in order to implement a combined digital systems of high-speed data paths with multi-bit operands and random logic circuits for state machines and bit-wise operations. For accelerating simulated annealing based FPGA placement algorithm, range limiter has been proposed to control the distance of two blocks to be interchanged. However, it is not applicable to MGRAs due to the heterogeneous structure of MGRAs. Proposed range limiter using connection bounding box effectively keeps the size of range limiter to encourage moves across fine-grain blocks in non-adjacent clusters. From experimental results, the proposed method achieved 47.8% reduction of cost in the best case compared with conventional methods.

A Reed-Solomon (RS) decoder is designed based on the pipelined recursive Euclidean algorithm in the key equation solution. While the Euclidean algorithm uses less Galois multipliers than the modified Euclidean (ME) and reformulated inversionless Berlekamp-Massey (RiBM) algorithms, division between two elements in Galois field is required. By implementing the division with a multi-cycle Galois inverter and a serial Galois multiplier, the proposed key equation solver architecture achieves lower complexity than the conventional ME and RiBM based architectures. The proposed RS (255,239) decoder reduces the hardware complexity by 25.9% with 6.5% increase in decoding latency.

In this paper, we present a GPU implementation of bulk multiple-length multiplications. The idea of our GPU implementation is to adopt a warp-synchronous programming technique. We assign each multiple-length multiplication to one warp that consists of 32 threads. In parallel processing using multiple threads, usually, it is costly to synchronize execution of threads and communicate within threads. In warp-synchronous programming technique, however, execution of threads in a warp can be synchronized instruction by instruction without any barrier synchronous operations. Also, inter-thread communication can be performed by warp shuffle functions without accessing shared memory. The experimental results show that our GPU implementation on NVIDIA GeForce GTX 980 attains a speed-up factor of 52 for 1024-bit multiple-length multiplication over the sequential CPU implementation. Moreover, we use this 1024-bit multiple-length multiplication for larger size of bits as a sub-routine. The GPU implementation attains a speed-up factor of 21 for 65536-bit multiple-length multiplication.

Protanopes and deuteranopes are difficult to distinguish some color pairs. In this letter, a new lightness modification method which considers the Craik-O'Brien effect is proposed. The lightness modification is performed at parts which are difficult to distinguish in the protanopia or deuteranopia. Experiments show the validity of the proposed method.

In this paper, we propose a digital image enlargement method based on a fuzzy technique that improves half-pixel generation, especially for convex and concave signals. The proposed method is a modified version of the image enlargement scheme previously proposed by the authors, which achieves accurate half-pixel interpolation and enlarges the original image by convolution with the Lanczos function. However, the method causes impulse-like artifacts in the enlarged image. In this paper, therefore, we introduce a fuzzy set and fuzzy rule for generating half-pixels to improve the interpolation of convex and concave signals. Experimental results demonstrate that, in terms of image quality, the proposed method shows superior performance compared to bicubic interpolation and our previous method.

To resist algebraic and fast algebraic attacks, Boolean functions used in stream ciphers should have optimal algebraic immunity and good fast algebraic immunity. One challenge of cryptographic Boolean functions is to determine their ability to resist fast algebraic attacks, which can be measured by their fast algebraic immunities. In this letter, we determine the exact values of fast algebraic immunity of the majority function of 2m and 2m+1 variables. This is the first time that the exact values of the fast algebraic immunity of an infinite class of symmetric Boolean functions with optimal algebraic immunity are determined.

This paper develops the generating function method for the discrete-time nonlinear optimal control problem. This method can analytically give the optimal input as state feedforward control in terms of the generating functions. Since the generating functions are nonlinear, we also develop numerical implementations to find their Taylor series expressions. This finally gives optimal solutions expressed only in terms of the pre-computed generating function coefficients and state boundary conditions, such that it is useful for the on-demand optimal solution generation for different boundary conditions. Examples demonstrate the effectiveness of the developed method.

For the nonlinear acoustic echo cancellation, we present an algorithm to estimate the threshold of the clipping effect and the room impulse response vector by suppressing their time-varying cost function. A common way to suppress the time-varying cost function of a pair of parameters is to alternatingly minimize the function with respect to each parameter while keeping the other fixed, which we refer to as adaptive alternating minimization. However, since the cost function for the threshold is nonconvex, the conventional methods approximate the exact minimizations by gradient descent updates, which causes serious degradation of the estimation accuracy in some occasions. In this paper, by exploring the fact that the cost function for the threshold becomes piecewise quadratic, we propose to exactly minimize the cost function for the threshold in a closed form while suppressing the cost function for the impulse response vector in an online manner, which we call exact-online adaptive alternating minimization. The proposed method is expected to approximate more efficiently the adaptive alternating minimization strategy than the conventional methods. Numerical experiments demonstrate the efficacy of the proposed method.

In a network with dense deployment of multiple-input multiple-output (MIMO) small cells, coverage overlap between the small cells produces intercell-interference, which degrades system capacity. This paper proposes an intercell-interference management (IIM) scheme that aims to maximize system capacity by using both power control for intercell-interference coordination (ICIC) on the transmitter side and interference cancellation (IC) on the receiver side. The power control determines transmit power levels at the base stations (BSs) by employing a neural network (NN) algorithm over the backhaul. To further improve the signal to interference plus noise ratio (SINR), every user terminal (UT) employs a multiuser detector (MUD) as IC. The MUD detects not only the desired signals, but also some interfering signals to be cancelled from received signals. The receiver structure consists of branch metric generators (BMGs) and MUD. BMGs suppress residual interference and noise in the received signals by whitening matched filters (WMFs), and then generate metrices by using the WMFs' outputs and symbol candidates that the MUD provides. On the basis of the metrices, the MUD detects both the selected interfering signals and the desired signals. In addition, the MUD determines which interfering signals are detected by an SINR based replica selection algorithm. Computer simulations demonstrate that the SINR based replica selection algorithm, which is combined with channel encoders and packet interleavers, can significantly improve the system bit error rate (BER) and that combining IC at the receiver with NN power control at the transmitter can considerably increase the system capacity. Furthermore, it is shown that choosing the detected interfering signals by the replica selection algorithm can obtain system capacity with comparable loss and less computational complexity compared to the conventional greedy algorithm.

We have proposed composite films composed of a molecular-aligned polymer and liquid crystal (LC) for substrate-free liquid crystal displays with high-contrast images. We successfully controlled the molecular alignment of the LC and formed molecular-aligned LC droplets in the polymer by controlling the fluidity of the LC/monomer mixture and the curing rate of the monomer.

In this letter, we propose a method for obtaining a clear and natural output image by tuning the illumination component in an input image. The proposed method is based on the retinex process and it is suitable for the image quality improvement of images of which illumination is insufficient.

Diabetes mellitus is a group of metabolic diseases that cause high blood sugar due to functional problems with the pancreas or metabolism. Diabetic patients have few subjective symptoms and may experience decreased sensation without being aware of it. The commonly performed tests for sensory disorders are qualitative in nature. The authors pay attention to the decline of the sensitivity of tactile sensations, and develop a non-invasive method to detect the level of tactile sensation using a novel micro-vibration actuator that employs shape-memory alloy wires. Previously, we performed a pilot study that applied the device to 15 diabetic patients and confirmed a significant reduction in the tactile sensation in diabetic patients when compared to healthy subjects. In this study, we focus on the asymptomatic development of decreased sensation associated with diabetes mellitus. The objectives are to examine diabetic patients who are unaware of abnormal or decreased sensation using the quantitative tactile sensation measurement device and to determine whether tactile sensation is decreased in patients compared to healthy controls. The finger method is used to measure the Tactile Sensation Threshold (TST) score of the index and middle fingers using the new device and the following three procedures: TST-1, TST-4, and TST-8. TST scores ranged from 1 to 30 were compared between the two groups. The TST scores were significantly higher for the diabetic patients (P<0.05). The TST scores for the left fingers of diabetic patients and healthy controls were 5.9±6.2 and 2.7±2.9 for TST-1, 15.3±7.0 and 8.7±6.4 for TST-4, and 19.3±7.8 and 12.7±9.1 for TST-8. Our data suggest that the use of the new quantitative tactile sensation measurement device enables the detection of decreased tactile sensation in diabetic patients who are unaware of abnormal or decreased sensation compared to controls.

How to manage the video streaming in future networks is becoming a more and more challenging issue. Recent studies on vehicular networks depict a new picture of the next generation Intelligent Transport System (ITS), with high level road safety and more comfortable driving experience. To cope with the heterogeneous network development for the next generation cellular network, centralized medium control is promising to be employed upon Road Side Unit (RSU). To accommodate the QoS constraints posed by video services in vehicular networks, the scalable video coding (SVC) scheme in H.264/AVC standard family offers spatial and temporal scalabilities in the video dissemination. In this paper, we target the resource allocation and layer selection problem for the multi-user video streaming over highway scenario, by employing SVC coding scheme for the video contents. We propose a Resource Allocation and Layer Selection (RALS) algorithm, which explicitly takes account of the utility value of each Group Of Picture (GOP) among all the vehicular users. Simulation results show that our proposed RALS algorithm outperforms the comparison schemes in typical scenarios.

This paper proposes an efficient lossless coding scheme for color video in RGB 4:4:4 format. For the R signal that is encoded before the other signals at each frame, we employ a block-adaptive prediction technique originally developed for monochrome video. The prediction technique used for the remaining G and B signals is extended to exploit inter-color correlations as well as inter- and intra-frame ones. In both cases, multiple predictors are adaptively selected on a block-by-block basis. For the purpose of designing a set of predictors well suited to the local properties of video signals, we also explore an appropriate setting for the spatiotemporal partitioning of a video volume.