Most existing deterministic multithreading systems are costly on pipeline parallel programs due to load imbalance. In this letter, we propose a Load-Balanced Deterministic Runtime (LBDR) for pipeline parallelism. LBDR deterministically takes some tokens from non-synchronization-intensive threads to synchronization-intensive threads. Experimental results show that LBDR outperforms the state-of-the-art design by an average of 22.5%.

We report a real time method to monitor the chemical reaction in microdroplets, which contain an organic dye, 5(6)-carboxynaphthofluorescein and a CdSe/ZnS quantum dot using fluorescence spectra. Especially, the relationship between the droplet size and the reaction rate of the two reagents was investigated by changing an injection speed.

We present a time-to-digital converter (TDC) achieving sub-picosecond resolution and high precision for all-digital phase-locked-loops (ADPLLs). The basic idea is using a charge pump to translate time interval into charge, and a successive-approximation-register-analog-to-digital converter (SAR-ADC) to quantize the charge. With this less complex configuration, high resolution, high precision, low power, and small area can be achieved all together. We analyzed the noise contribution from the charge pump and describe detailed design and implementation for sizing the capacitor and transistors, with the awareness of noise and linearity. The analysis demonstrates the proposed TDC capable of sub-picosecond resolution and high precision. Two prototype chips were fabricated in 65nm CMOS with 0.06mm2, and 0.018mm2 core areas, respectively. The achieved resolutions are 0.84ps and 0.80ps, in 8-bit and 10-bit range, respectively. The measured single-shot-precisions range from 0.22 to 0.6ps, and from 0.66 to 1.04ps, respectively, showing consistent trends with the analysis. Compared with state-of-the-arts, best performance balance has been achieved.

This paper presents an analog front-end circuit for a 60-GHz proximity wireless communication receiver. The feature of the proposed analog front-end circuit is a bandwidth more than 1-GHz wide. To expand the bandwidth of a low-pass filter and a voltage gain amplifier, a technique to reduce the parasitic capacitance of a transconductance amplifier is proposed. Since the bandwidth is also limited by on-resistance of the ADC sampling switch, a switch separation technique for reduction of the on-resistance is also proposed. In a high-speed ADC, the SNDR is limited by the sampling jitter. The developed high resolution VCO auto tuning effectively reduces the jitter of PLL. The prototype is fabricated in 65nm CMOS. The analog front-end circuit achieves over 1-GHz bandwidth and 27.2-dB SNDR with 224mW Power consumption.

Least squares error (LSE) method adopted recursively can be used to track the frequency and amplitude of signals in steady states and kinds of non-steady ones in power system. Taylor expansion is used to give another version of this recursive LSE method. Aided by variable-windowed short-time discrete Fourier transform, recursive LSEs with and without Taylor expansion converge faster than the original ones in the circumstance of off-nominal input singles. Different versions of recursive LSE were analyzed under various states, such as signals of off-nominal frequency with harmonics, signals with step changes, signals modulated by a sine signal, signals with decaying DC offset and additive Gaussian white noise. Sampling rate and data window size are two main factors influencing the performance of method recursive LSE in transient states. Recursive LSE is sensitive to step changes of signals, but it is in-sensitive to signals' modulation and singles with decaying DC offset and noise.

In this letter, a robust time synchronization algorithm is proposed for MIMO-OFDM based WLAN systems. IEEE 802.11ac MIMO-OFDM WLAN standard specifies that the preamble with cyclic shift diversity (CSD) scheme is used for time and frequency synchronization. However, since the CSD scheme introduces multiple cross-correlation peaks at the receiver, serious performance degradation appears if the conventional cross-correlation based algorithm is applied. In the proposed algorithm, the time synchronization error due to multiple peaks is compensated by adding the cross-correlation value to its reverse cyclic-shifted version. Simulation results show that the proposed algorithm achieves an SNR gain of 1.5 to 4.5dB for the synchronization failure rate of 10-2 compared with the existing algorithms.

With the rapid growth of high performance ICT (Information Communication Technologies) devices such as smart phones and tablet PCs, multitasking has become one of the popular ways of using mobile devices. The reasons users have adopted multitask operation are that it reduces the level of dissatisfaction regarding waiting time and makes effective use of time by switching their attention from the waiting process to other content. This is a good solution to the problem of waiting; however, it may cause another problem, which is the increase in traffic volume due to the multiple applications being worked on simultaneously. Thus, an effective method to control throughput adapted to the multitasking situation is required. This paper proposes a transmission rate control method for web browsing that takes multitasking behavior into account and quantitatively demonstrates the effect of service by two different field experiments. The main contribution of this paper is to present a service design process for a new transmission rate control that takes into account human-network interaction based on the human-centered approach. We show that the degree of satisfaction in relation to waiting time did not degrade even when a field trial using a testbed showed that throughput of the background task was reduced by 40%.

For a large-sized touch screen, we designed and evaluated a real-time touch microarchitecture using a field-programmable gate array (FPGA). A high-speed hardware accelerator based on a parallel touch algorithm is suggested and implemented in this letter. The touch controller also has a timing control unit and an analog digital convert (ADC) control unit for analog touch sensing circuits. Measurement results of processing time showed that the touch controller with its proposed microarchitecture is five times faster than the 32-bit reduced instruction set computer (RISC) processor without the touch accelerator.

Network traffic load usually differs significantly at different times of a day due to users' different time-preference. Network congestion may happen in traffic peak times. In order to prevent this from happening, network service providers (NSPs) can either over-provision capacity for demand at peak times of the day, or use dynamic time-dependent pricing (TDP) scheme to reduce the demand at traffic peak times. Since over-provisioning network capacity is costly, many researchers have proposed TDP schemes to control congestion as well as to improve the revenue of NSPs. To the best of our knowledge, all the studies on TDP schemes consider only the monopoly or duopoly NSP case. In our previous work, the duopoly NSP case has been studied with the assumption that each NSP has complete information of quality of service (QoS) of the other NSP. In this paper, an oligopoly NSP case is studied. NSPs try to maximize their overall revenue by setting time-dependent price, while users choose NSPs by considering their own time preference, congestion status in the networks and the price set by the NSPs. The interactions among NSPs are modeled as an oligopoly Bertrand game. Firstly, assuming that each NSP has complete information of QoS of all NSPs, a unique Nash equilibrium of the game is established under the assumption that users' valuation of QoS is uniformly distributed. Secondly, the assumption of complete information of QoS of all NSPs is relaxed, and a learning algorithm is proposed for NSPs to achieve the Nash equilibrium of the game. Analytical and experimental results show that NSPs can benefit from TDP scheme, however, not only the competition effect but also the incomplete information among NSPs causes revenue loss for NSPs under the TDP scheme.

Computing and power resources are often limited in real-time embedded control systems. In this paper, we resolve the trade-off problem between control performance and power consumption in a real-time embedded control system with a dynamic voltage and frequency scaling (DVFS) uniprocessor implementing multiple control tasks. We formulate an optimization problem whose cost function depends on both the control performance and the power consumption. We introduce an adapter into the real-time embedded control system that adaptively assigns deadlines of jobs and clock frequencies according to the plant's stability and schedulability by solving the optimization problem. In numerical simulations, we show that the proposed adapter can reduce the power consumption while maintaining the control performance.

Cognitive radio has been developed recently as a promising solution to tackle the spectrum related issues such as spectrum scarcity and spectrum underutilization. Cognitive spectrum assignment is necessary for allocating spectrum bands to secondary users in order to avoid conflicts among secondary users and maximize the total network performance under a given set of conditions. In most spectrum assignment schemes, throughput is considered as the main criterion for spectrum selection or spectrum assignment. In this paper, we propose a distortion-aware channel allocation scheme for multiple secondary users who compete for primary channels to transmit multimedia data. In the proposed scheme, idle spectrum bands are assigned to the multimedia secondary users that attain the highest video distortion reduction. The scheme is expected to mitigate the selfish behaviors of users in competing channels. The performance effectiveness of our proposed channel allocation scheme is demonstrated through simulation by comparing with a benchmark of two reference spectrum assignment schemes.

Although multi-user multiple-input multiple-output (MI-MO) systems provide high data rate transmission, they may suffer from interference. Block diagonalization and eigenbeam-space division multiplexing (E-SDM) can suppress interference. The transmitter needs to determine beamforming weights from channel state information (CSI) to use these techniques. However, MIMO channels change in time-varying environments during the time intervals between when transmission parameters are determined and actual MIMO transmission occurs. The outdated CSI causes interference and seriously degrades the quality of transmission. Channel prediction schemes have been developed to mitigate the effects of outdated CSI. We evaluated the accuracy of prediction of autoregressive (AR)-model-based prediction and Lagrange extrapolation in the presence of channel estimation error. We found that Lagrange extrapolation was easy to implement and that it provided performance comparable to that obtained with the AR-model-based technique.

In consideration of the image noise captured by photoelectric cameras at nighttime, a robust motion detection algorithm based on sparse representation is proposed in this study. A universal dictionary for arbitrary scenes is presented. Realistic and synthetic experiments demonstrate the robustness of the proposed approach.

Industrial applications such as automotive ones require a cheap communication mechanism to send out communication messages from node to node by their deadline time. This paper presents a design paradigm in which we optimize both assignment of a network node to a bus and slot multiplexing of a FlexRay network system under hard real-time constraints so that we can minimize the cost of wire harness for the FlexRay network system. We present a cost minimization problem as a non-linear model. We developed a network synthesis tool which was based on simulated annealing. Our experimental results show that our design paradigm achieved a 50.0% less cost than a previously proposed approach for a virtual cost model.

Simulating the mobility of mobile devices has always been an important issue as far as wireless networks are concerned because mobility needs to be taken into account in various situations in wireless networks. Researchers have been trying, for many years, to improve the accuracy and flexibility of mobility models. Although recent progress of designing mobility models based on social graph have enhanced the performance of mobility models and made them more convenient to use, we believe the accuracy and flexibility of mobility models could be further improved by taking a more integrated structure as the input. In this paper, we propose a new way of designing mobility models on the basis of relational graph [1] which is a graph depicting the relation among objects, e.g. relation between people and people, and also people and places. Moreover, some novel mobility features were introduced in the proposed model to provide social, spatial and temporal properties in order to produce results similar to real mobility data. It was demonstrated by simulation that these measures could generate results similar to real mobility data.

This paper presents a framework for reducing the energy consumption of embedded real-time systems. We implemented the presented framework as both an optimization toolchain and an energy-aware real-time operating system. The framework consists of the integration of multiple techniques to optimize the energy consumption. The main idea behind our approach is to utilize trade-offs between the energy consumption and the performance of different processor configurations during task checkpoints, and to maintain memory allocation during task context switches. In our framework, a target application is statically analyzed at both intra-task and inter-task levels. Based on these analyzed results, runtime optimization is performed in response to the behavior of the application. A case study shows that our toolchain and real-time operating systems have achieved energy reduction while satisfying the real-time performance. The toolchain has also been successfully applied to a practical application.

In this paper, a real-time medium access control (MAC) protocol based on a coding-black-burst mechanism with low latency and high energy efficiency is proposed for wireless sensor networks. The Black-Burst (BB) mechanism is used to provide real-time access. However, when the traffic load is heavy, BB will cause a lot of energy loss and latency due to its large length. A binary coding mechanism is applied to BB in our coding-black-burst-based protocol to reduce the energy consumption and latency by at least (L-2(log2 L+1)) for L-length BB. The new mechanism also gives priority to the real-time traffic with longer waiting delays to access the channel. The theoretical analysis and simulation results indicate that our protocol provides low end-to-end delay and high energy efficiency for real-time communication.

In this paper, we present an efficient time-of-arrival (TOA)-based localization method for wireless sensor networks. The goal of a localization system is to accurately estimate the geographic location of a wireless device. In real wireless sensor networks, accurately estimating mobile device location is difficult because of the presence of various errors. Therefore, localization methods have been studied in recent years. In indoor environments, the accuracy of wireless localization systems is affected by non-line-of-sight (NLOS) errors. The presence of NLOS errors degrades the performance of wireless localization systems. In order to effectively estimate the location of the mobile device, NLOS errors should be recognized and mitigated in indoor environments. In the TOA-based ranging method, the distance between the two wireless devices can be computed by multiplying a signal's propagation delay time by the speed of light. TOA-based localization measures the distance between the mobile station (MS) and three or more base stations (BSs). However, each of the NLOS errors of the measured distance between the i-th BS and the MS is different due to dissimilar obstacles in the direct signal path between the two nodes. In order to accurately estimate the location in a TOA-based localization system, an optimized localization algorithm that selects three measured distances with fewer NLOS errors is necessary. We present an efficient TOA-based localization scheme that combines three selected BSs in wireless sensor networks. This localization scheme yields improved localization performance in wireless sensor networks. In this paper, performance tests are performed, and the simulation results are verified through comparisons between various localization methods and the proposed method. As a result, proposed localization scheme using BS selection achieves remarkably better localization performance than the conventional methods. This is verified by experiments in real environments, and demonstrates a performance analysis in NLOS environments. By using BS selection, we will show an efficient and effective TOA-based localization scheme in wireless sensor networks.

In this paper, we introduce a parallax barrier system that shows high definition autostereoscopy and holds wide viewing zone. The proposed method creates a 4-view parallax barrier system with full display resolution per view by setting aperture ratio to one quarter and using time-division quadplexing, then applies obtained 4-view to 2-view, so that the viewing zone for each eye becomes wider than that from the conventional methods. We build a prototype with two 120,Hz LCD panels and manage to achieve continuous viewing zone with common head-tracking device involved. However, moire patterns and flickers stand out, which are respectively caused by the identical alignments of the color filters on the overlaid LCD panels and a lack of refresh rate of 240,Hz. We successfully remove the moire patterns by changing the structure of the system and inserting a diffuser. We also reduce the flickers by proposing 1-pixel aperture, while stripe shaped noise due to the lack of refresh rate occurs during a blink or a saccade. The stripe noise can be effectively weakened by applying green and magenta anaglyph to the proposed system, where extra crosstalk takes place since the default RGB color filters on LCD panels share certain ranges of wavelength with each other. Although a trade-off turns out to exist between stripe noise and crosstalk from our comparison experiment, results from different settings all hold acceptable quality and show high practicability of our method. Furthermore, we propose a solution that shows possibility to satisfy both claims, where extra color filters with narrow bandwidths are required.

Vector processors have significant advantages for next generation multimedia applications (MMAs). One of the advantages is that vector processors can achieve high data transfer performance by using a high bandwidth memory sub-system, resulting in a high sustained computing performance. However, the high bandwidth memory sub-system usually leads to enormous costs in terms of chip area, power and energy consumption. These costs are too expensive for commodity computer systems, which are the main execution platform of MMAs. This paper proposes a new multi-banked cache memory for commodity computer systems called MVP-cache in order to expand the potential of vector architectures on MMAs. Unlike conventional multi-banked cache memories, which employ one tag array and one data array in a sub-cache, MVP-cache associates one tag array with multiple independent data arrays of small-sized cache lines. In this way, MVP-cache realizes less static power consumption on its tag arrays. MVP-cache can also achieve high efficiency on short vector data transfers because the flexibility of data transfers can be improved by independently controlling the data transfers of each data array.