This paper studies mapping techniques of multiple applications on embedded many-core SoCs. The mapping techniques proposed in this paper are static which means the mapping is decided at design time. The mapping techniques take into account both inter-application and intra-application parallelism in order to fully utilize the potential parallelism of the many-core architecture. Additionally, the proposed static mapping supports dynamic application switching, which means the applications mapped onto the same cores are switched to each other at runtime. Two approaches are proposed for static mapping: one approach is based on integer linear programming and the other is based on a greedy algorithm. Experimental results show the effectiveness of the proposed techniques.

Self-aligned four-terminal (4T) planar metal double-gate (DG) polycrystalline-silicon (poly-Si) thin-film transistors (TFTs) were fabricated on a glass substrate at a low temperature (LT), which is below $550^{circ}$C, to realize high performance and low power dissipation system-on-glass (SoG). The top gate (TG) and bottom gate (BG) were formed from tungsten (W); the BG was embedded in the glass substrate and the TG was fabricated by a self-alignment process using the BG as a photomask. This structure is called embedded metal double-gate (E-MeDG) in this paper. The poly-Si channel with lateral large grains was fabricated using a continuous-wave laser lateral crystallization (CLC). The self-aligned 4T E-MeDG LT poly-Si TFT, with a gate length of 5,$mu $m and TG and BG SiO$_2$ thicknesses of 50 and 100,nm, respectively, exhibited a subthreshold swing of 120,mV/dec and a threshold voltage ($mathrm{V}_{mathrm{th}}$) of $-$0.5,V in the connecting DG mode; i.e. when TG is connected to BG. In the TG operation at various BG control voltage, a threshold voltage modulation factor $(gamma = Delta mathrm{V}_{mathrm{th}}/Delta mathrm{V}_{mathrm{BG}})$ of 0.47 at negative BG control voltage and 0.60 at positive BG control voltage are demonstrated, which values are nearly equal to theoretical prediction of 0.40 and 0.75. Trend of subthreshold swing (s.s.) of TG operation under different BG control voltage are also consistent with theoretical prediction. In addition to TG operation, successful BG operation under various TG control voltages was confirmed. Field-effect mobility derived from g$_{mathrm{m}}$ also varied depending on control gate voltage. The high controllability of device parameter of individual LT poly-Si TFTs is caused by excellent crystalline quality of CLC poly-Si film and will enable us to the fabrication of high-speed and low power-dissipation SoG.

In conventional wireless cellular networks, cell coverage is static and fixed, and each user equipment (UE) is connected to one or a few local base stations (BS). However, the users' distribution in the network area commonly fluctuates during a day. When there are congeries of users in some areas, conventional networks waste idle network resources in sparse areas. To address this issue, we propose a novel approach for cooperative cluster formation to dynamically transfer idle network resources from sparse cells to crowded cells or hotspots. In our proposed scheme, BS coverage is directed to hotspots by dynamically changing the antennas' beam angles, and forming large optimal cooperative clusters around hotspots. In this study, a cluster is a group of BSs that cooperatively perform joint transmission (JT) to several UEs. In this paper, a mathematical framework for calculation of the system rate of a cooperative cluster is developed. Next, the set of BSs for each cluster and the antennas' beam angles of each BS are optimized so that the system rate of the network is maximized. The trend of performance variation versus cluster size is studied and its limitations are determined. Numerical results using 3GPP specifications show that the proposed scheme attains several times higher capacity than conventional systems.

Due to the recent network service market trends, network infrastructure providers must make their network infrastructures tolerant of network service complexity and swift at providing new network services. To achieve this, we first make a design decision for the single domain network infrastructure in which we use network virtualization and separate the network service control and management from the network infrastructure and leave the resource connectivity control and management in the network infrastructure so that the infrastructure can maintain simplicity and the network service can become complex and be quickly provided. Along with the decision, we construct an architecture of the network infrastructure and a network management model. The management model defines a slice as being determined by abstracted resource requirements and restructures the roles and planes from the viewpoint of network infrastructure usability so that network service requesters can manage network resources freely and swiftly in an abstract manner within the authorities the network infrastructure operator provides. We give the details of our design and implementation for a network virtualization management system along with the model. We deployed and evaluated our designed and implemented management system on the Japan national R&E testbed (JGN-X) to confirm the feasibility of our management system design and discuss room for improvement in terms of response time and scalability towards practical use. We also investigated certain cases of sophisticated network functions to confirm that the infrastructure can accept these functions without having to be modified.

Aircraft Landing Scheduling (ALS) attempts to determine the landing time for each aircraft. The objective of ALS is to minimise the deviations of the landing time of each aircraft from its target landing time. In this paper, we propose a dynamic hyper-heuristic algorithm for the ALS problem. In our approach, the Scatter Search algorithm is chosen as the high level heuristic to build a chain of intensification and diversification priority rules, which are applied to generate the landing sequence by different priority rules, which are low level heuristics in the hyper-heuristic framework. The landing time for each aircraft can be calculated efficiently based on the landing sequence. Simulation studies demonstrate that the proposed algorithm can obtain high quality solutions for ALS.

This paper presents a $24 imes24$ MIMO channel sounder that has been developed based on a scalable fully parallel MIMO architecture. It can be flexibly configured with 3 sub-transmitters and 3 sub-receivers, each of which consists of 8 RF ports. This flexibility allows the measurement for both purposes of double directional and multi-link MIMO channel measurements. Implementation issues related to the multi-link operation on the fully parallel architecture were successfully solved by appropriate system design and applying several calibration techniques. The performance of the developed system was validated by extensive test experiments. Finally, a multi-link channel measurement example in an indoor environment was presented demonstrating the capability of the proposed system.

This paper aims to achieve a high-quality exposure level quantification of whole-body average-specific absorption rates (WBA-SARs) for small animals in a medium-size reverberation chamber (RC). A two-step method, which incorporates the finite-difference time-domain (FDTD) numerical solutions with electric field measurements in an RC-type exposure system, has been used as an evaluation method to determine the whole-body exposure level in small animals. However, there is little data that quantitatively demonstrate the validity and accuracy of this method in an RC up to now. In order to clarify the validity of the two-step method, we compare the physical quantities in terms of electric field strength and WBA-SARs by using a direct numerical assessment method known as the method of moments (MoM) with ten homogenous gel phantoms placed in an RC with 2GHz exposure. The comparison results show that the relative errors between the two-step method and the MoM approach are approximately below 10%, which reveals the validity and usefulness of the two-step technique. Finally, we perform a dosimetric analysis of the WBA-SARs for anatomical mouse models with the two-step method and determine the input power related to our developed RC-exposure system to achieve a target exposure level in small animals.

In this paper, we propose a modified-error adaptive feedback active noise control (ANC) system using a linear prediction filter. The proposed ANC system is advantageous in terms of the rate of convergence, while maintaining stability, because it can reduce narrowband noise while suppressing disturbance, including wideband components. The estimation accuracy of the noise control filter in the conventional system is degraded because the disturbance corrupts the input signal to the noise control filter. A solution of this problem is to utilize a linear prediction filter. The linear prediction filter is utilized for the modified-error feedback ANC system to suppress the wideband disturbance because the linear prediction filter can separate narrowband and wideband noise. Suppressing wideband noise is important for the head-mounted ANC system we have already proposed for reducing the noise from a magnetic resonance imaging (MRI) device because the error microphones are located near the user's ears and the user's voice consequently corrupts the input signal to the noise control filter. Some simulation and experimental results obtained using a digital signal processor (DSP) demonstrate that the proposed feedback ANC system is superior to a conventional feedback ANC system in terms of the estimation accuracy and the rate of convergence of the noise control filter.

Runtime analysis is to enhance the safety of critical systems by monitoring the change of corresponding external environments. In this paper, a modified FTA approach, making full utilization of the existing safety analysis result, is put forward to achieve runtime safety analysis. The procedures of the approach are given in detail. This approach could be widely used in safety engineering of critical systems.

To secure a wireless sensor and actuator network (WSAN) in cyber-physical systems, trust management framework copes with misbehavior problem of nodes and stimulate nodes to cooperate with each other. The existing trust management frameworks can be classified into reputation-based framework and trust establishment framework. There, however, are still many problems with these existing trust management frameworks, which remain unsolved, such as frangibility under possible attacks. To design a robust trust management framework, we identify the attacks to the existing frameworks, present the countermeasures to them, and propose a hybrid trust management framework (HTMF) to construct trust environment for WSANs in the paper. HTMF includes second-hand information and confidence value into trustworthiness evaluation and integrates the countermeasures into the trust formation. We preform extensive performance evaluations, which show that the proposed HTMF is more robust and reliable than the existing frameworks.

In a sector of a single cell, due to the fading characteristic of wireless channels, several decode-and-forward relay stations are deployed to form a two-hop relay-assisted multicast system. We propose two schemes for the system, the first scheme combines the use of space-time code and distributed space-time code (DSTC), and the second one combines the use of DSTC and maximum ratio combining. We give an outage probability analysis for both of them. Based on this analysis, we manage to maximize the spectral efficiency under a preset outage probability confinement by finding out the optimal power allocation and relay location strategies. We use genetic algorithms to verify our analysis and numerical results show that the schemes proposed by us significantly outperform the scheme in previous work. We also show the effect of path loss exponent on the optimal strategy.

In the optimization of decision diagrams, variable reordering approaches are often used to minimize the number of nodes. However, such approaches are less effective for analysis of multi-state systems given by monotone structure functions. Thus, in this paper, we propose algorithms to minimize the number of edges in an edge-valued multi-valued decision diagram (EVMDD) for fast analysis of multi-state systems. The proposed algorithms minimize the number of edges by grouping multi-valued variables into larger-valued variables. By grouping multi-valued variables, we can reduce the number of nodes as well. To show the effectiveness of the proposed algorithms, we compare the proposed algorithms with conventional optimization algorithms based on a variable reordering approach. Experimental results show that the proposed algorithms reduce the number of edges by up to 15% and the number of nodes by up to 47%, compared to the conventional ones. This results in a speed-up of the analysis of multi-state systems by about three times.

It is known that the IP Multimedia Subsystem (IMS) provides various telecom services e.g., VoIP, instant messaging, and video conferencing. In the IMS, these services are provided with session initiation protocol (SIP) handled by call/session control function servers (CSCFs). Completing the SIP signaling call flow without delay is vital to provide satisfactory services to the users. For service continuity, previous studies redundantly synchronized session states of CSCFs with backup servers. This paper proposes an IMS restoration system that selectively stores the session states. This is achieved by utilizing the retransmission mechanism of SIP. Time-based simulation emulating the process of backup servers shows that the proposed system reduces the number of backup servers to less than 38% compared to the previous studies, without degrading the service quality.

Visual quality evaluation is crucially important for various video and image processing systems. Traditionally, subjective image quality assessment (IQA) given by the judgments of people can be perfectly consistent with human visual system (HVS). However, subjective IQA metrics are cumbersome and easily affected by experimental environment. These problems further limits its applications of evaluating massive pictures. Therefore, objective IQA metrics are desired which can be incorporated into machines and automatically evaluate image quality. Effective objective IQA methods should predict accurate quality in accord with the subjective evaluation. Motivated by observations that HVS is highly adapted to extract irregularity information of textures in a scene, we introduce multifractal formalism into an image quality assessment scheme in this paper. Based on multifractal analysis, statistical complexity features of nature images are extracted robustly. Then a novel framework for image quality assessment is further proposed by quantifying the discrepancies between multifractal spectrums of images. A total of 982 images are used to validate the proposed algorithm, including five type of distortions: JPEG2000 compression, JPEG compression, white noise, Gaussian blur, and Fast Fading. Experimental results demonstrate that the proposed metric is highly effective for evaluating perceived image quality and it outperforms many state-of-the-art methods.

We design a full-order observer for discrete-time linear time-invariant systems with constant output delays. The observer design is based on the output delay model expressed by a two-dimensional state variable, with discrete-time and space independent variables. Employing a discrete-time state transformation, we construct an explicit strict Lyapunov function that enables us to prove the global exponential stability of the full-order observer error system with an explicit estimate of the exponential decay rate. The numerical example demonstrates the design of the full-order observer and illustrates the validity of the exponential stability.

An accurate time-of-arrival (TOA) estimation method for isolated pulses positioning system is proposed in this paper. The method is based on a multi-level crossing timing (MCT) digitizer and least square (LS) criterion, namely LS-MCT method, in which TOA of the received signal is directly described as a parameterized combination of a set of MCT samples of the leading and trailing edges of the signal. The LS-MCT method performs a receiver training process, in which a GPS synchronized training pulse generator (TPG) is used to obtain training data and determine the parameters of the TOA combination. The LS method is then used to optimize the combination parameters with a minimization criterion. The proposed method is compared to the conventional TOA estimation methods such as leading edge level crossing discriminator (LCD), adaptive thresholding (ATH), and signal peak detection (PD) methods. Simulation results show that the proposed algorithm leads to lower sensitivity to signal-to-noise ratio (SNR) and attains better TOA estimation accuracy than available TOA methods.

The excessively high temperature in a chip may cause circuit malfunction and performance degradation, and thus should be avoided to improve system reliability. In this paper, a novel oscillation-based on-chip thermal sensing architecture for dynamically adjusting supply voltage and clock frequency in System-on-a-Chip (SoC) is proposed. It is shown that the oscillation frequency of a ring oscillator reduces linearly as the temperature rises, and thus provides a good on-chip temperature sensing mechanism. An efficient Dynamic Voltage-to-Frequency Scaling (DF2VS) algorithm is proposed to dynamically adjust supply voltage according to the oscillation frequencies of the ring oscillators distributed in SoC so that thermal sensing can be carried at all potential hot spots. An on-chip Dynamic Voltage Scaling or Dynamic Voltage and Frequency Scaling (DVS or DVFS) monitor selects the supply voltage level and clock frequency according to the outputs of all thermal sensors. Experimental results on SoC benchmark circuits show the effectiveness of the algorithm that a 10% reduction in supply voltage alone can achieve about 20% power reduction (DVS scheme), and nearly 50% reduction in power is achievable if the clock frequency is also scaled down (DVFS scheme). The chip temperature will be significant lower due to the reduced power consumption.

The data rate of VLSI interconnections has been increasing according to the demand for high-speed operation of semiconductors such as CPUs. To realize high performance VLSI systems, high-speed data communication has become an important factor. However, at high-speed data rates, it is difficult to achieve accurate communication without bit errors because of inter-symbol interference (ISI). This paper presents high-speed data communication techniques for VLSI systems using Tomlinson-Harashima Precoding (THP). Since THP can eliminate the ISI with limiting average and peak power of transmitter signaling, THP is suitable for implementing advanced low-voltage VLSI systems. In this paper, 4-PAM (Pulse amplitude modulation) with THP has been employed to achieve high-speed data communication in VLSI systems. Simulation results show that THP can remove the ISI without increasing peak and average power of a transmitter. Moreover, simulation results clarify that multiple-valued data communication is very effective to reduce implementation costs for realizing high-speed serial links.

Feedback data loss can severely degrade overall system performance. In addition, it can affect the control and computation of the Cyber-physical Systems (CPS). CPS hold enormous potential for a wide range of emerging applications that include different data traffic patterns. These data traffic patterns have wide varieties of diversities. To recover various traffic patterns we need to know the nature of their underlying property. In this paper, we propose a data recovery framework for different traffic patterns of CPS, which comprises data pre-processing step. In the proposed framework, we designed a Data Pattern Analyzer to classify the different patterns and built a model based on the pattern as a data pre-processing step. Inside the framework, we propose a data recovery scheme, called Efficient Temporal and Spatial Data Recovery (ETSDR) algorithm to recover the incomplete feedback for CPS to maintain real time control. In this algorithm, we utilize the temporal model based on the traffic pattern and consider the spatial correlation of the nearest neighbor sensors. Numerical results reveal that the proposed ETSDR outperforms both the weighted prediction (WP) and the exponentially weighted moving average (EWMA) algorithms regardless of the increment percentage of missing data in terms of the root mean square error, the mean absolute error, and the integral of absolute error.

This paper studies an adaptive high gain observer design for nonlinear systems which have lower triangular nonlinearity with Lipschitz coefficient, depending on the control input. Because the gain of the proposed observer is tuned automatically by a simple update law, our design approach doesn't need any information about the Lipschitz constant. Also, it is shown that under some assumptions, the dynamic gain of the proposed observer is bounded and its estimation error converges to zero asymptotically. Finally, a numerical example is given to verify the effectiveness of our design approach.