Big data analysis and a data storing applications require a huge volume of storage and a high I/O performance. Applications can achieve high level of performance and cost efficiency by exploiting the high I/O performance of direct attached storages (DAS) such as internal HDDs. With the size of stored data ever increasing, it will be difficult to replace servers since internal HDDs contain huge amounts of data. Generally, the data is copied via Ethernet when transferring the data from the internal HDDs to the new server. However, the amount of data will continue to rapidly increase, and thus, it will be hard to make these types of transfers through the Ethernet since it will take a long time. A storage area network such as iSCSI can be used to avoid this problem because the data can be shared with the servers. However, this decreases the level of performance and increases the costs. Improving the flexibility without incurring I/O performance degradation is required in order to improve the DAS architecture. In response to this issue, we propose FlexDAS, which improves the flexibility of direct attached storage by using a disk area network (DAN) without degradation the I/O performance. A resource manager connects or disconnects the computation nodes to the HDDs via the FlexDAS switch, which supports the SAS or SATA protocols. This function enables for the servers to be replaced in a short period of time. We developed a prototype FlexDAS switch and quantitatively evaluated the architecture. Results show that the FlexDAS switch can disconnect and connect the HDD to the server in just 1.16 seconds. We also confirmed that the FlexDAS improves the performance of the data intensive applications by up to 2.84 times compared with the iSCSI.

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.

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.

Address configuration is a key problem in data center networks. The core issue of automatic address configuration is assigning logical addresses to the physical network according to a blueprint, namely logical-to-device ID mapping, which can be formulated as a graph isomorphic problem and is hard. Recently years, some work has been proposed for this problem, such as DAC and ETAC. DAC adopts a sub-graph isomorphic algorithm. By leveraging the structure characteristic of data center network, DAC can finish the mapping process quickly when there is no malfunction. However, in the presence of any malfunctions, DAC need human effort to correct these malfunctions and thus is time-consuming. ETAC improves on DAC and can finish mapping even in the presence of malfunctions. However, ETAC also suffers from some robustness and efficiency problems. In this paper, we present GA-MAP, a data center networks address mapping algorithm based on genetic algorithm. By intelligently leveraging the structure characteristic of data center networks and the global search characteristic of genetic algorithm, GA-MAP can solve the address mapping problem quickly. Moreover, GA-MAP can even finish address mapping when physical network involved in malfunctions, making it more robust than ETAC. We evaluate GA-MAP via extensive simulation in several of aspects, including computation time, error-tolerance, convergence characteristic and the influence of population size. The simulation results demonstrate that GA-MAP is effective for data center addresses mapping.

Survivability is the capability of a system to provide its services in a timely manner even after intrusion and compromise occur. In this paper, we focus on the quantitative analysis of survivability of virtual machine (VM) based intrusion tolerant system in the presence of Byzantine failures due to malicious attacks. Intrusion tolerant system has the ability of a system to continuously provide correct services even if the system is intruded. This paper introduces a scheme of the intrusion tolerant system with virtualization, and derives the success probability for one request by a Markov chain under the environment where VMs have been intruded due to a security hole by malicious attacks. Finally, in numerical experiments, we evaluate the performance of VM-based intrusion tolerant system from the viewpoint of survivability.

The crossbar-based switch fabric is widely used in today's high performance switches, due to its internally nonblocking and simply implementation properties. Usually there are two main switching architectures for crossbar-based switch fabric: internally bufferless crossbar switch and crosspoint buffered crossbar switch. As internally bufferless crossbar switch requires a complex centralized scheduler which limits its scalability to high speeds, crosspoint buffered crossbar switch has gained more attention because of its simpler distributed scheduling algorithm and better switching performance. However, almost all the scheduling algorithms proposed previously for crosspoint buffered crossbar switch either have unsatisfactory scheduling performance under non-uniform traffic patterns or show poor service fairness between input traffic flows. In order to overcome the disadvantages of existing algorithms, in this paper we propose two novel high performance scheduling algorithms named MCQF_RR and IMCQF_RR for crosspoint buffered crossbar switches. Both algorithms have a time complexity of O(log N), where N is the number of input/output ports of the switch. MCQF_RR takes advantage of the combined weight information about queue length and service waiting time of input queues to perform scheduling. In order to further reduce the scheduling complexity and make it feasible for high speed switches, IMCQF_RR uses the compressed queue length information instead of original queue length information to schedule cells in input VOQs. Simulation results show that our novel scheduling algorithms MCQF_RR and IMCQF_RR can demonstrate excellent delay performance comparable to existing high performance scheduling algorithms under both uniform and non-uniform traffic patterns, while maintain good service fairness performance under severe non-uniform traffic patterns.

In this paper, we propose a patch-wise learning based approach to deal with the multiple-shot people re-identification task. In the proposed approach, re-identification is formulated as a patch-wise set-to-set matching problem, with each patch set being matched using a specifically learned Mahalanobis distance metric. The proposed approach has two advantages: (1) a patch-wise representation that moderates the ambiguousness of a non-rigid matching problem (of human body) to an approximate rigid one (of body parts); (2) a patch-wise learning algorithm that enables more constraints to be included in the learning process and results in distance metrics of high quality. We evaluate the proposed approach on popular benchmark datasets and confirm its competitive performance compared to the state-of-the-art methods.

This paper presents a 20GHz Class-C VCO using a noise sensitivity mitigation technique. A radio frequency Class-C VCO suffers from the AM-PM conversion, caused by the non-linear capacitance of cross coupled pair. In this paper, the phase noise degradation mechanism is discussed, and a desensitization technique of AM-PM noise is proposed. In the proposed technique, AM-PM sensitivity is canceled by tuning the tail impedance, which consists of 4-bit resistor switches. A 65-nm CMOS prototype of the proposed VCO demonstrates the oscillation frequency from 19.27 to 22.4GHz, and the phase noise of -105.7dBc/Hz at 1-MHz offset with the power dissipation of 6.84mW, which is equivalent to a Figure-of-Merit of -183.73dBc/Hz.

We present a low-voltage digitally-controlled oscillator (DCO) with the third-order ΔΣ modulator utilized in the medical implant communication service (MICS) frequency band. An optimized DCO core operating in the subthreshold region is designed, based on the gm/ID methodology. Thermometer coder with the dynamic element matching and ΔΣ modulator are implemented for the frequency tuning. High frequency resolution is achieved by using the ΔΣ modulator. The ΔΣ-modulator-based LC-DCO implemented in a 130-nm CMOS technology has achieved the phase noise of -115.3 dBc/Hz at 200 kHz offset frequency with the tuning range of 382 MHz to 412 MHz for the MICS band. It consumes 700 µW from a 0.7-V supply voltage and has a high frequency resolution of 18 kHz.

In recent times, wireless Local Area Networks (wireless LANs) based on the IEEE 802.11 standard have been spreading rapidly, and connecting to the Internet using wireless LANs has become more common. In addition, public wireless LAN service areas, such as train stations, hotels, and airports, are increasing and tethering technology has enabled smartphones to act as access points (APs). Consequently, there can be multiple APs in the same area. In this situation, users must select one of many APs. Various studies have proposed and evaluated many AP selection methods; however, existing methods do not consider AP mobility. In this paper, we propose an AP selection method based on cooperation among APs and user movement. Moreover, we demonstrate that the proposed method dramatically improves throughput compared to an existing method.

Data stored in non-volatile memories may be destructed due to crosstalk and radiation but we can restore their data by using error-correcting codes. However, non-volatile memories consume a large amount of energy in writing. How to reduce maximum writing bits even using error-correcting codes is one of the challenges in non-volatile memory design. In this paper, we first propose Doughnut code which is based on state encoding limiting maximum and minimum Hamming distances. After that, we propose a code expansion method, which improves maximum and minimum Hamming distances. When we apply our code expansion method to Doughnut code, we can obtain a code which reduces maximum-flipped bits and has error-correcting ability equal to Hamming code. Experimental results show that the proposed code efficiently reduces the number of maximum-writing bits.

In this paper, the repeatable hybrid parallel implementation of inverse matrix computation using SMW formula is proposed. The authors' had previously proposed a hybrid parallel algorithm for inverse matrix computation. It is reasonably fast for a one time computation of an inverse matrix, but it is hard to apply this algorithm repeatedly for consecutive computations since the relocation of the large matrix is required at the beginning of each iterations. In order to eliminate the relocation of the large input matrix which is the output of the inverse matrix computation from the previous time step, the computation algorithm has been redesigned so that the required portion of the input matrix becomes the same as the output portion of the previously computed matrix in each node. This makes it possible to repeatedly and efficiently apply the SMW formula to compute inverse matrix in a time-series simulation.

Content centric networking (CCN) is a newly proposed futuristic Internet paradigm in which communication depends on the decoupling of content names from their locations. In CCN-based multihop wireless ad hoc networks, the participating nodes show dynamic topology, intermittent connectivity, channels fluctuation, and severe constraints such as limited battery power. In the case of traffic congestion, the affected nodes die early owing to the shortage of battery power. Consequently, all pending request entries are also destroyed, which further degrades the network performance as well as the node working lifetime. In this study, we have proposed a novel energy aware transmission scheme in which the forwarding mechanism is based on a node's residual energy. The proposed scheme is evaluated using official ndnSIM. This scheme enhances performance in terms of content retrieval time and total Interest transmission in the network.

A method for measuring the magnetic field strength for human exposure assessment closer than 20cm to wireless power transfer (WPT) systems for information household appliances is investigated based on numerical simulations and measurements at 100kHz and 6.78MHz. Four types of magnetic sources are considered: a simple 1-turn coil and three types of coils simulating actual WPT systems. A magnetic sensor whose cross sectional area is 100cm2 as prescribed in International Electrotechnical Commission 62233 is used. Simulation results show that the magnetic field strength detected by the magnetic sensor is affected by its placement angle. The maximum coefficient of variation (CV) is 27.2% when the magnetic source and the sensor are in contact. The reason for this deviation is attributable to the localization of the magnetic field distribution around the magnetic source. The coupling effect between the magnetic source and the sensor is negligible. Therefore, the sensor placement angle is an essential factor in magnetic field measurements. The CV due to the sensor placement angle is reduced from 21% to 4% if the area of the sensor coil is reduced from 100 to 0.75cm2 at 6.78MHz. However, the sensitivity of the sensor coil is decreased by 42.5dB. If measurement uncertainty that considers the deviation in the magnetic field strength due to the sensor placement angle is large, the measured magnetic field strength should be corrected by the uncertainty. If the magnetic field distribution around the magnetic source is known, conservative exposure assessments can be achieved by placing the magnetic sensor in locations at which the spatial averaged magnetic field strengths perpendicular to the magnetic sensor coils become maximum.

As the use of information technology is rapidly expanding, the power consumption of IT equipment is becoming an important social issue. As such, the power supply of IT equipment must provide various power saving measures through advanced features. A digitally controlled power supply is attractive for satisfying this requirement due to its flexibility and advanced management functionality. However, a digitally controlled power supply has issues with its transient response performance because the conversion time of the analog-digital converter and the time required for digital processing in the digital controller adversely affect the dynamic characteristics. The present paper introduces a new approach that can improve the transient response performance of the digital point-of-load (POL) power supplies of computer processors. The resulting power systems use feed-forward transient control, in addition to the general voltage regulation feedback control loop, to improve their dynamic characteristics. On the feed-forward control path, the processor workload information is supplied to the power supply controller from the processor. The power supply controller uses the workload information to predict the power load change and generates an auxiliary control to improve the transient response performance. As the processor workload information, the processor-integrated performance counter values are sent to the power supply controller via a hardware interface. The processor power consumption prediction equation is modeled using the moving average model, which uses performance counter values of several past steps. The prediction equation parameters are defined by multiple regression analysis using the measured CPU power consumption data and experimentally obtained performance counter information. The analysis reveals that the optimum parameters change with time during transient periods. The modeled equation well explains the processor power load change. The measured CPU power consumption profile is confirmed to be accurately replicated by the prediction for a period of 200ns. Using the power load change prediction model, circuit simulations of the feed-forward transient control are conducted. It is validated that the proposed approach improves power supply transient response under some practical server workloads.

A conventional HMM-based speech synthesis system for Hanoi Vietnamese often suffers from hoarse quality due to incomplete F0 parameterization of glottalized tones. Since estimating F0 from glottalized waveform is rather problematic for usual F0 extractors, we propose a pitch marking algorithm where pitch marks are propagated from regular regions of a speech signal to glottalized ones, from which complete F0 contours for the glottalized tones are derived. The proposed F0 parameterization scheme was confirmed to significantly reduce the hoarseness whilst slightly improving the tone naturalness of synthetic speech by both objective and listening tests. The pitch marking algorithm works as a refinement step based on the results of an F0 extractor. Therefore, the proposed scheme can be combined with any F0 extractor.

A novel approach for the multiple-model multi-sensor Bernoulli filter (MM-MSBF) based on the theory of finite set statistics (FISST) is proposed for a single maneuvering target tracking in the presence of detection uncertainty and clutter. First, the FISST is used to derive the multi-sensor likelihood function of MSBF, and then combining the MSBF filter with the interacting multiple models (IMM) algorithm to track the maneuvering target. Moreover, the sequential Monte Carlo (SMC) method is used to implement the MM-MSBF algorithm. Eventually, the simulation results are provided to demonstrate the effectiveness of the proposed filter.

In this paper, we analyze a cooperative communication network with multi energy-harvesting and decode-and-forward relays in which the best relay is selected based on criteria such as Maximizing First-Hop Signal to Noise Ratios (SNRs) (MFHS protocol), Maximizing Second-Hop SNRs (MSHS protocol), and Maximizing End-to-End SNRs (MEES protocol). In these protocols, the relays apply power-splitting receivers to harvest energy from radio frequency signals emitted from a source. Thus, each received SNR in the second hop is a function of a direct relay-destination gain and an indirect source-relay gain. The system performance of the proposed protocols is evaluated via exact outage probability analyses and Monte Carlo simulations. For further comparisons, an energy-harvesting decode-and-forward scheme with randomly relay selection (RRS protocol) and an energy-harvesting amplify-and-forward scheme (BAF protocol) are investigated and discussed. The simulation results show that 1) the MEES protocol outperforms the MFHS and MSHS protocols, and the MFHS protocol is more efficient than the MSHS protocol in the low SNR regions; 2) the proposed protocols achieve the best performance at the specific optimal power splitting ratios for which the MEES protocol has a balanced ratio for energy harvesting and decoding capacity; and 3) the theoretical analyses agree well with the simulation results.

In this paper, we propose a localization algorithm that uses the time difference of arrival (TDOA) and the angle of arrival (AOA). The problem is formulated in a hybrid linear matrix equation. TDOA and AOA measurements are used for estimating the target's position. Although it is known that the accuracy of TDOA based localization is superior to that of AOA based localization, TDOA based localization has a poor vertical accuracy in deteriorated geometrical conditions. This paper, therefore, proposes a localization algorithm in which the vertical position is estimated by AOA measurements and the horizontal position is estimated by TDOA measurement in order to achieve high location accuracy in three dimensions. In addition, the Lagrange multipliers are obtained efficiently and robustly. The simulation analysis shows that the proposed constrained linear squares (CLS) algorithm is an unbiased estimator, and that it approaches the Cramer-Rao lower bound (CRLB) when the measurement noise and the sensor's location errors are sufficiently small.

We consider the distributed source coding system of two correlated Gaussian Vector sources Yl=t(Yl1, Yl2),l=1,2 which are noisy observations of correlated Gaussian scalar source X0. We assume that for each (l,k)∈{1,2}, Ylk is an observation of the source X0, having the form Ylk=X0+Nlk, where Nlk is a Gaussian random variable independent of X0. We further assume that Nlk, (l,k)∈{1,2}2 are independent. In this system two correlated Gaussian observations are separately compressed by two encoders and sent to the information processing center. We study the remote source coding problem where the decoder at the center attempts to reconstruct the remote source X0. The determination problem of the rate distortion region for this communication system can be regarded as an extension of the Gaussian CEO problem to the case of vector observations. For each vector observation we can obtain an estimation on X0 from this observation. Those estimations are sufficient statistics on X0. Using those sufficient statistics, we determine the rate distortion region by showing that it coincides with the rate distortion region of the CEO problem where the scalar observations of X0 are equal to the estimations computed from the vector observations. We further extend the result to the case of L terminal and general vector observations.