With the development of cloud computing, the Mobile Edge Computing has emerged and attracted widespread attentions. In this paper, we focus on the load balancing in MEC with energy harvesting. We first introduce the load balancing in MEC as a problem of minimizing both the energy consumption and queue redundancy. Thereafter, we adapt such a optimization problem to the Lyapunov algorithm and solve this optimization problem. Finally, extensive simulation results validate that the obtained strategy improves the capabilities of MEC systems.

We propose a video authentication scheme to verify whether a given video file is recorded by a camera device or touched by a video editing tool. The proposed scheme prepares software characteristics of camera devices and video editing tools in advance, and compares them with the metadata of the given video file. Through practical implementation, we show that the proposed scheme has benefits of fast analysis time, high accuracy and full automation.

Due to recent technology progress based on big-data processing, many applications present irregular or unpredictable communication patterns among compute nodes in high-performance computing (HPC) systems. Traditional communication infrastructures, e.g., torus or fat-tree interconnection networks, may not handle well their matchmaking problems with these newly emerging applications. There are already many communication-efficient application mapping algorithms for these typical non-random network topologies, which use nearby compute nodes to reduce the network distances. However, for the above unpredictable communication patterns, it is difficult to efficiently map their applications onto the non-random network topologies. In this context, we recommend using random network topologies as the communication infrastructures, which have drawn increasing attention for the use of HPC interconnects due to their small diameter and average shortest path length (ASPL). We make a comparative study to analyze the impact of application mapping performance on non-random and random network topologies. We propose using topology embedding metrics, i.e., diameter and ASPL, and list several diameter/ASPL-based application mapping algorithms to compare their job scheduling performances, assuming that the communication pattern of each application is unpredictable to the computing system. Evaluation with a large compound application workload shows that, when compared to non-random topologies, random topologies can reduce the average turnaround time up to 39.3% by a random connected mapping method and up to 72.1% by a diameter/ASPL-based mapping algorithm. Moreover, when compared to the baseline topology mapping method, the proposed diameter/ASPL-based topology mapping strategy can reduce up to 48.0% makespan and up to 78.1% average turnaround time, and improve up to 1.9x system utilization over random topologies.

Low Earth Orbit (LEO) satellite networks serve as a powerful complement to the terrestrial networks because of their ability to provide global coverage. In LEO satellite networks, the network is prone to congestion due to several reasons. First, the terrestrial gateways are usually located within a limited region leading to congestion of the nodes near the gateways. Second, routing algorithms that merely adopt shortest paths fail to distribute the traffic uniformly in the network. Finally, the traffic input may exceed the network capacity. Therefore, rate control and load-balancing routing are needed to alleviate network congestion. Moreover, different kinds of traffic have different Quality of Service (QoS) requirements which need to be treated appropriately. In this paper, we investigate joint rate control and load-balancing routing in LEO satellite networks to tackle the problem of network congestion while considering the QoS requirements of different traffic. The joint rate control and routing problem is formulated with the throughput and end-to-end delay requirements of the traffic taken into consideration. Two routing schemes are considered which differ in whether or not different traffic classes can be assigned different paths. For each routing scheme, the joint rate control and routing problem is formulated. A heuristic algorithm based on simulated annealing is proposed to solve the problems. Besides, a snapshot division method is proposed to increase the connectivity of the network and reduce the number of snapshots by merging the links between satellites and gateways. The simulation results show that compared with methods that perform routing and rate control separately, the proposed algorithm improves the overall throughput of the network and provides better QoS guarantees for different traffic classes.

Multiscale retinex is one of the most popular image enhancement methods. However, its control parameters, such as Gaussian kernel sizes, gain, and offset, should be tuned carefully according to the image contents. In this letter, we propose a new method that optimizes the parameters using practical swarm optimization and multi-objective function. The method iteratively verifies the visual quality (i.e. brightness, contrast, and colorfulness) of the enhanced image using a multi-objective function while subtly adjusting the parameters. Experimental results shows that the proposed method achieves better image quality qualitatively and quantitatively compared with other image enhancement methods.

In an internet of things (IoT) system using an energy harvesting device and a secondary (2nd) battery, regardless of the age of the 2nd battery, the power management shortens the lifespan of the entire system. In this paper, we propose a scheme that extends the lifetime of the energy harvesting-based IoT system equipped with a Lithium 2nd battery. The proposed scheme includes several policies of using a supercapacitor as a primary energy storage, limiting the charging level according to the predicted harvesting energy, swinging the energy level around the minimum stress state of charge (SOC) level, and delaying the charge start time. Experiments with natural solar energy measurements based on a battery aging approximation model show that the proposed method can extend the operation lifetime of an existing IoT system from less than one and a half year to more than four years.

With the rapid development of multimedia, violent video can be easily accessed in games, movies, websites, and so on. Identifying violent videos and rating violence extent is of great importance to media filtering and children protection. Many previous studies only address the problems of violence scene detection and violent action recognition, yet violence rating problem is still not solved. In this paper, we present a novel video-level rating prediction method to estimate violence extent automatically. It has two main characteristics: (1) a two-stream network is fine-tuned to construct effective representations of violent videos; (2) a violence rating prediction machine is designed to learn the strength relationship among different videos. Furthermore, we present a novel violent video dataset with a total of 1,930 human-involved violent videos designed for violence rating analysis. Each video is annotated with 6 fine-grained objective attributes, which are considered to be closely related to violence extent. The ground-truth of violence rating is given by pairwise comparison method. The dataset is evaluated in both stability and convergence. Experiment results on this dataset demonstrate the effectiveness of our method compared with the state-of-art classification methods.

Network throughput has become an important issue for big-data analysis on Warehouse-Scale Computing (WSC) systems. It has been reported that randomly-connected inter-switch networks can enlarge the network throughput. For irregular networks, a multi-path routing method called k-shortest path routing is conventionally utilized. However, it cannot efficiently exploit longer-than-shortest paths that would be detour paths to avoid bottlenecks. In this work, a novel routing method called k-optimized path routing to achieve high throughput is proposed for irregular networks. We introduce a heuristic to select detour paths that can avoid bottlenecks in the network to improve the average-case network throughput. Experimental results by network simulation show that the proposed k-optimized path routing can improve the saturation throughput by up to 18.2% compared to the conventional k-shortest path routing. Moreover, it can reduce the computation time required for optimization to 1/2760 at a minimum compared to our previously proposed method.

Stochastic computing (SC), which is an approximate computation with probabilities, has attracted attention owing to its small area, small power consumption and high fault tolerance. In this paper, we focus on the transient fault tolerance of SC based on linear finite state machines (linear FSMs). We show that state assignment of FSMs considerably affects the fault tolerance of linear FSM-based SC circuits, and present a Markov model for representing the impact of the state assignment on the behavior of faulty FSMs and estimating the expected error significance of the faulty FSM-based SC circuits. Furthermore, we propose a heuristic algorithm for appropriate state assignment that can mitigate the influence of transient faults. Experimental analysis shows that the state assignment has an impact on the transient fault tolerance of linear FSM-based SC circuits and the proposed state assignment algorithm can achieve a quasi-optimal state assignment in terms of high fault tolerance.

This article proposes a dynamic linkage service which is a specific service model of integrated broadcast — broadband services based ATSC 3.0. The dynamic linkage service is useful to the viewer who wants to continue watching programs using TV or their personal devices, even after the terrestrial broadcast ends due to the start of the next regular programming. In addition, we verify the feasibility of the proposed extended dynamic linkage service through developed emulation system based on ATSC 3.0. In consideration of the personal network capabilities of the viewer environment, the service was tested with 4K/2K Ultra HD and receiving the service was finished within 4 second over intranet.

Data sorting is an important operation in computer science. It is extensively used in several applications such as database and searching. While high-performance sorting accelerators are in demand, it is very important to pay attention to the hardware resources for such kind of high-performance sorters. In this paper, we propose three FPGA based architectures to accelerate sorting operation based on the merge sorting algorithm. We call our proposals as WMS: Wide Merge Sorter, EHMS: Efficient Hardware Merge Sorter, and EHMSP: Efficient Hardware Merge Sorter Plus. We target the Virtex UltraScale FPGA device. Evaluation results show that our proposed merge sorters maintain both the high-performance and cost-effective properties. While using much fewer hardware resources, our proposed merge sorters achieve higher performance compared to the state-of-the-art. For instance, with 256 sorted records are produced per cycle, implementation results of proposed EHMS show a significant reduction in the required number of Flip Flops (FFs) and Look-Up Tables (LUTs) to about 66% and 79%, respectively over the state-of-the-art merge sorter. Moreover, while requiring fewer hardware resources, EHMS achieves about 1.4x higher throughput than the state-of-the-art merge sorter. For the same number of produced records, proposed WMS also achieves about 1.6x throughput improvement over the state-of-the-art while requiring about 81% of FFs and 76% of LUTs needed by the state-of-the-art sorter.

The authors have been investigating the deterioration process of Au-plated slip-ring and Ag-Pd brush system with lubricant to realize stable and long lifetime. Through the past tests, it can be made clear that lubricant is very important for long lifetime, and a simple model of the deterioration process was proposed. However, it is still an issue how the lubricant is deteriorated and also what the relation between lubricant deterioration and contact voltage behavior is. In this paper, the contact voltage waveforms were regularly recorded during the test, and analyzed to obtain the time change of peak voltage and standard deviation during one rotation. Based on these results, it is discussed what happens at the interface between ring and brush with the lubricant. And the following results are made clear. The fluctuation of voltage waveforms, especially peaks of pulse-like fluctuation more easily occurs for minus rings than for plus rings. Further, peak values of the pulse-like fluctuation rapidly decreases and disappear at lower rotation speed as mentioned in the previous works. In addition, each peaks of the pulse-like fluctuation is identified at each position of the ring periphery. From these results, it can be assumed that lubricant film exists between brush and ring surface and electric conduction is realized by tunnel effect. In other words, it can be made clear that the fluctuation would be caused by the lubricant layer, not only by the ring surface. Finally, an electric conduction model is proposed and the above results can be explained by this model.

This paper proposes an image inpainting algorithm based on multiple linear models and matrix rank minimization. Several inpainting algorithms have been previously proposed based on the assumption that an image can be modeled using autoregressive (AR) models. However, these algorithms perform poorly when applied to natural photographs because they assume that an image is modeled by a position-invariant linear model with a fixed model order. In order to improve inpainting quality, this work introduces a multiple AR model and proposes an image inpainting algorithm based on multiple matrix rank minimization with sparse regularization. In doing so, a practical algorithm is provided based on the iterative partial matrix shrinkage algorithm, with numerical examples showing the effectiveness of the proposed algorithm.

An inpainting method via sparse representation based on a new phaseless quality metric is presented in this paper. Since power spectra, phaseless features, of local regions within images enable more successful representation of their texture characteristics compared to their pixel values, a new quality metric based on these phaseless features is newly derived for image representation. Specifically, the proposed method enables spare representation of target signals, i.e., target patches, including missing intensities by monitoring errors converged by phase retrieval as the novel phaseless quality metric. This is the main contribution of our study. In this approach, the phase retrieval algorithm used in our method has the following two important roles: (1) derivation of the new quality metric that can be derived even for images including missing intensities and (2) conversion of phaseless features, i.e., power spectra, to pixel values, i.e., intensities. Therefore, the above novel approach solves the existing problem of not being able to use better features or better quality metrics for inpainting. Results of experiments showed that the proposed method using sparse representation based on the new phaseless quality metric outperforms previously reported methods that directly use pixel values for inpainting.

In this paper, we aim to develop technologies for the circuit fault diagnosis and propose a formulation of a measure of a test pattern for the circuit fault diagnosis. Given a faulty circuit, the fault diagnosis is to deduce locations of faults that had occurred in the circuit. The fault diagnosis is executed in software before the failure analysis by which engineers inspect physical defects, and helps to improve the manufacturing process which yielded faulty circuits. The heart of the fault diagnosis is to distinguish between candidate faults by using test patterns, which are applied to the circuit-under-diagnosis (CUD), and thus test patterns that can distinguish as many faults as possible need to be generated. This fact motivates us to consider the test pattern measure based on the number of fault-pairs that become distinguished by a test pattern. To the best of the authors' knowledge, that measure requires the computational time of complexity order O(NF2), where NF denotes the number of candidate faults. Since NF is generally large for real industrial circuits, the computational time of the measure is long even when a high-performance computer is used. The formulation proposed in this paper makes it possible to calculate the measure in the computational complexity of O(NF log NF), and thus that measure is useful for the test pattern selection in the fault diagnosis. In computational experiments, the effectiveness of the formulation is demonstrated as samples of computational times of the measure calculated by the traditional and the proposed formulae and thorough comparisons between several greedy heuristics which are based on the measure.

This paper summarizes our recent studies on architecture, photonic integration, system validation and networking performance analysis of a flexible low-latency interconnect optical network switch (Flex-LIONS) for datacenter and high-performance computing (HPC) applications. Flex-LIONS leverages the all-to-all wavelength routing property in arrayed waveguide grating routers (AWGRs) combined with microring resonator (MRR)-based add/drop filtering and multi-wavelength spatial switching to enable topology and bandwidth reconfigurability to adapt the interconnection to different traffic profiles. By exploiting the multiple free spectral ranges of AWGRs, it is also possible to provide reconfiguration while maintaining minimum-diameter all-to-all interconnectivity. We report experimental results on the design, fabrication, and system testing of 8×8 silicon photonic (SiPh) Flex-LIONS chips demonstrating error-free all-to-all communication and reconfiguration exploiting different free spectral ranges (FSR0 and FSR1, respectively). After reconfiguration in FSR1, the bandwidth between the selected pair of nodes is increased from 50Gb/s to 125Gb/s while an all interconnectivity at 25Gb/s is maintained using FSR0. Finally, we investigate the use of Flex-LIONS in two different networking scenarios. First, networking simulations for a 256-node datacenter inter-rack communication scenario show the potential latency and energy benefits when using Flex-LIONS for optical reconfiguration based on different traffic profiles (a legacy fat-tree architecture is used for comparison). Second, we demonstrate the benefits of leveraging two FSRs in an 8-node 64-core computing system to provide reconfiguration for the hotspot nodes while maintaining minimum-diameter all-to-all interconnectivity.

Two-ray (TR) fading model is one of the fading models to represent a worst-case fading scenario. We derive the exact closed-form expressions of the generalized moment generating function (G-MGF) for the TR fading model, which enables us to analyze the numerous types of wireless communication applications. Among them, we carry out several analytical results for the TR fading model, including the exact ergodic capacity along with asymptotic expressions and energy detection performance. Finally, we provide numerical results to validate our evaluations.

Through novel rotation writing method of Bragg grating in multicore fiber, its strain vector characteristics are analyzed. The relation between the rotation angle and the strain curvature sensitivity is obtained. Reconstruction of strain vector is verified.

When using a gesture-based interface for pointing to targets on a wide screen, displaying a large pointer instead of a typical spot pattern reduces disturbance caused by measurement errors of user's pointing posture. However, it remains unclear why a large pointer helps facilitate easy pointing. To examine this issue, in this study we propose a mathematical model that formulates human pointing motions affected by a large pointer. Our idea is to describe the effect of the large pointer as human visual perception, because the user will perceive the pointer-target distance as being shorter than it actually is. We embedded this scheme, referred to as non-linear distance filter (NDF), into a typical feedback loop model designed to formulate human pointing motions. We also proposed a method to estimate NDF mapping from pointing trajectories, and used it to investigate the applicability of the model under three typical disturbance patterns: small vibration, smooth shift, and step signal. Experimental results demonstrated that the proposed NDF-based model could accurately reproduced actual pointing trajectories, achieving high similarity values of 0.89, 0.97, and 0.91 for the three respective disturbance patterns. The results indicate the applicability of the proposed method. In addition, we confirmed that the obtained NDF mappings suggested rationales for why a large pointer helps facilitate easy pointing.

For low-density parity-check (LDPC) codes, the penalized decoding method based on the alternating direction method of multipliers (ADMM) can improve the decoding performance at low signal-to-noise ratios and also has low decoding complexity. There are three effective methods that could increase the ADMM penalized decoding speed, which are reducing the number of Euclidean projections in ADMM penalized decoding, designing an effective penalty function and selecting an appropriate layered scheduling strategy for message transmission. In order to further increase the ADMM penalized decoding speed, through reducing the number of Euclidean projections and using the vertical layered scheduling strategy, this paper designs a fast converging ADMM penalized decoding method based on the improved penalty function. Simulation results show that the proposed method not only improves the decoding performance but also reduces the average number of iterations and the average decoding time.