Performance Of Real-time Applications Research Articles

Hydrogen passivation: a proficient strategy to enhance the optical and photoelectrochemical performance of InGaN/GaN single-quantum-well nanorods

Recently, III-nitride semiconductor nanostructures, especially InGaN/GaN quantum well nanorods (NRs), have been established as a promising material of choice for nanoscale optoelectronics and photoelectrochemical (PEC) water-splitting applications. Due to the large number of surface states, III-nitride NRs suffer from low quantum efficiency. Therefore, control of the surface states is necessary to improve device performance in real-time applications. In this work, we investigated the effect of hydrogen plasma treatment on the optical properties of InGaN/GaN single-quantum-well (SQW) NRs. The low-temperature photoluminescence (PL) studies revealed that yellow and green emissions overlapped and the yellow band is more dominant in the pristine InGaN/GaN SQW NRs. However, the emission corresponding to yellow luminescence was strongly suppressed and the green emission is more intensified in hydrogenated InGaN/GaN SQW NRs. Furthermore, the time-resolved PL spectroscopy studies revealed that the carrier lifetimes of hydrogenated InGaN/GaN SQW NRs are relatively short compared to the pristine InGaN/GaN SQW, indicating the effective reduction of non-radiative centers. From the PEC measurement, the photocurrent density of hydrogenated InGaN/GaN SQW NRs in the H2SO4 solution is found to be 5 mA cm−2 at −0.48 V versus reversible hydrogen electrode, which is 3.5-fold larger than that of pristine ones. These findings shed new light on the significance of surface treatment on the optical properties and thus nanostructured photoelectrodes for PEC applications.

A novel strategy for power sources management in connected plug-in hybrid electric vehicles based on mobile edge computation framework

This paper proposes a novel control framework and the corresponding strategy for power sources management in connected plug-in hybrid electric vehicles (cPHEVs). A mobile edge computation (MEC) based control framework is developed first, evolving the conventional on-board vehicle control unit (VCU) into the hierarchically asynchronous controller that is partly located in cloud. Elaborately contrastive analysis on the performance of processing capacity, communication frequency and communication delay manifests dramatic potential of the proposed framework in sustaining development of the cooperative control strategy for cPHEVs. On the basis of MEC based control framework, a specific cooperative strategy is constructed. The novel strategy accomplishes energy flow management between different power sources with incorporation of the active energy consumption plan and adaptive energy consumption management. The method to generate the reference battery state-of-charge (SOC) trajectories in energy consumption plan stage is emphatically investigated, fast outputting reference trajectories that are tightly close to results by global optimization methods. The estimation of distribution algorithm (EDA) is employed to output reference control policies under the specific terminal conditions assigned via the machine learning based method. Finally, simulation results highlight that the novel strategy attains superior performance in real-time application that is close to the offline global optimization solutions.

3D hand mesh reconstruction from a monocular RGB image

Most of the existing methods for 3D hand analysis based on RGB images mainly focus on estimating hand keypoints or poses, which cannot capture geometric details of the 3D hand shape. In this work, we propose a novel method to reconstruct a 3D hand mesh from a single monocular RGB image. Different from current parameter-based or pose-based methods, our proposed method directly estimates the 3D hand mesh based on graph convolution neural network (GCN). Our network consists of two modules: the hand localization and mask generation module, and the 3D hand mesh reconstruction module. The first module, which is a VGG16-based network, is applied to localize the hand region in the input image and generate the binary mask of the hand. The second module takes the high-order features from the first and uses a GCN-based network to estimate the coordinates of each vertex of the hand mesh and reconstruct the 3D hand shape. To achieve better accuracy, a novel loss based on the differential properties of the discrete mesh is proposed. We also use professional software to create a large synthetic dataset that contains both ground truth 3D hand meshes and poses for training. To handle the real-world data, we use the CycleGAN network to transform the data domain of real-world images to that of our synthesis dataset. We demonstrate that our method can produce accurate 3D hand mesh and achieve an efficient performance for real-time applications.

Vision‐based tip position tracking control of two‐link flexible manipulator

Owing to the non-collocation of actuators and sensors in a flexible-link manipulator (FLM) it becomes difficult to achieve accurate tip position tracking. To resolve this issue, a vision sensor is used for direct measurement of the tip position instead of employing the traditional mechanical sensors. Among the different visual servoing (VS) control schemes, image-based VS (IBVS) is more effective. However, there are many challenges in the IBVS scheme such as singularities in the interaction matrix and local minima in trajectories that affect the system performance in real-time applications. In this study, the moment-based new visual feature is selected to address the aforesaid issues that arise in the IBVS scheme. Furthermore, a new two-time scale IBVS controller is developed for addressing the tip-tracking control problem of the two-link flexible manipulator (TLFM). In the proposed control scheme, the dynamics of the FLM is decomposed into two-time scale models, namely a slow subsystem and a fast subsystem. The performance and robustness of the proposed new two-time scale IBVS controller for TLFM are verified by pursuing simulation studies. It is observed from the obtained results that the proposed controller effectively stabilises the oscillatory dynamics and tracks the reference trajectory accurately.

Performance Evaluation of IPv6 Network for Real-Time Applications using IS-ISv6 Routing Protocol on Riverbed Modeler

Abstract In this new era of the internet world, long-distance effective communication depends on the choice of IP and routing protocols. Various decisions are considered to find the optimal routing protocol for network deployment. The routing protocol which gives the best performance on some objective parameters (convergence, jitter, delay, bandwidth utilization, throughput, etc.) have opted for deployment. Also, according to the network and traffic demands, these routing protocols decide the performance of real-time applications. As IPv4 addresses are exhausting, moving to IPv6 is expected and challenging. This next-generation internet protocol brings new modified routing protocols which are enhanced versions of the existing ones. In this paper, the IS-ISv6 routing protocol is considered as it is scalable, more flexible towards IPv6 addresses, robust, support larger areas and can give better performance than other existing routing protocols. The IPv6 network is configured to measure the performance of real-time applications-voice and video using IS-ISv6 routing protocol and the network is simulated on riverbed modeler academic edition 17.5. The main objective of this paper is to find the performance of IS-ISv6 for routing the traffic. For both, the applications, the traffic sent and received are present to calculate the maximum throughput of the network. The results are also present for end-to- end delay and packet delay variations for voice and video applications. The simulation results for IPv6 traffic dropped and jitter in voice are also obtained in this paper. This research paper finds that the IS-ISv6 routing protocol enhances the throughput of video applications in the IPv6 network. However, the average performance for voice application is achieved with less end-to-end delay and packet delay variations. Thus IS-ISv6 routing protocol can be used efficiently for high-performance real-time application networks.

Cooperative control strategy for plug-in hybrid electric vehicles based on a hierarchical framework with fast calculation

Abstract Developing optimal control strategies with capability of real-time implementation for plug-in hybrid electric vehicles (PHEVs) has drawn explosive attention. In this study, a novel hierarchical control framework is proposed for PHEVs to achieve the instantaneous vehicle-environment cooperative control. The mobile edge computation units (MECUs) and the on-board vehicle control units (VCUs) are included as the distributed controllers, which enable vehicle-environment cooperative control and reduce the computation intensity on the vehicle by transferring partial work from VCUs to MECUs. On this basis, a novel cooperative control strategy is designed to successively achieve the energy management planned by the iterative dynamic programming (IDP) in MECUs and the energy utilization management achieved by the model predictive control (MPC) algorithm in the VCU. The performance of raised control strategy is validated by simulation analysis, highlighting that the cooperative control strategy can achieve superior performance in real-time application that is close to the global optimization results solved offline.

Impact of Channel Bonding on Network Performance in Real Time Applications

This paper investigates the impact of channel bonding property provided in wireless technology on performance in real-time applications. IEEE 802.11n is an amendment to the IEEE 802.11 Wireless Local Area Network (WLAN) standard, which aims to extensively improve network throughput over legacy WLANs. This new network technology provides a better performance for general Internet applications such as web service and file transfer. However, the recent network measurements show that real-time application traffic is consistently increasing in the Internet. Real-time applications such as Voice over IP (VoIP) or video conferencing requires distinct performance metrics compared to the general Internet services in that they prioritize delay, latency, and delay jitter rather than network throughput. This paper investigates how such real-time applications perform in IEEE 802.11n WLANs. Our indoor experiments show that 802.11n basically supports better service than the previous WLAN standards. The channel bonding technique in 802.11n further improves the performance even under mobile conditions.

Hardware implementation of digital image skeletonization algorithm using FPGA for computer vision applications

Nowadays embedded multimedia devices are designed for computationally intensive applications such as image processing in various multimedia systems. Image processing algorithms should be implemented on hardware platforms for improving the performance. Reconfigurable hardware implementation using Field Programmable Gate Arrays (FPGAs) provides low latency with high performance in real time applications. FPGAs offer the reprogrammability of an application specific solution while retaining the performance advantage. In real time applications as image sizes increase rapidly, only hardware systems must be used with low complex software. In this paper, main perspective of developing and implementing skeletonization algorithm as a part of computer vision, pattern recognition application is focused and presented. A simple algorithm to skeletonize the 2-D image using MATLAB is developed. An architecture and implementation of this skeletonization algorithm for 2-D gray scale images is proposed. For analyzing pixel values 3 × 3 windowing operator is used. The proposed architecture is tested for an image size of 8 × 8, but the approach presented in this paper can be used for images of any size (M × N), if the FPGA memory is sufficiently large. The implementation was carried out on Xilinx Vertex 5 board.

Preemption of the Partial Reconfiguration Process to Enable Real-Time Computing With FPGAs

To improve computing performance in real-time applications, modern embedded platforms comprise hardware accelerators that speed up the task’s most compute-intensive parts. A recent trend in the design of real-time embedded systems is to integrate field-programmable gate arrays (FPGA) that are reconfigured with different accelerators at runtime, to cope with dynamic workloads that are subject to timing constraints. One of the major limitations when dealing with partial FPGA reconfiguration in real-time systems is that the reconfiguration port can only perform one reconfiguration at a time: if a high-priority task issues a reconfiguration request while the reconfiguration port is already occupied by a lower-priority task, the high-priority task has to wait until the current reconfiguration is completed (a phenomenon known as priority inversion ), unless the current reconfiguration is aborted (introducing unbounded delays in low-priority tasks, a phenomenon known as starvation ). This article shows how priority inversion and starvation can be solved by making the reconfiguration process preemptive —that is, allowing it to be interrupted at any time and resumed at a later time without restarting it from scratch. Such a feature is crucial for the design of runtime reconfigurable real-time systems but not yet available in today’s platforms. Furthermore, the trade-off of achieving a guaranteed bound on the reconfiguration delay for low-priority tasks and the maximum delay induced for high-priority tasks when preempting an ongoing reconfiguration has been identified and analyzed. Experimental results on the Xilinx Zynq-7000 platform show that the proposed implementation of preemptive reconfiguration introduces a low runtime overhead, thus effectively solving priority inversion and starvation.

A COMPARATIVE STUDY OF QOS OVER IPV4/IPV6 USING OPNET MODELER

The increasing number of internet users around the world and their demand for multimedia applications like VoIP and video conference force the network providers to think about Quality of Services. Since these new applications are sensitive to network performance, the demand for larger bandwidth is increased especially when network parameters like Jitter, End to End (E2E) delay and Packet loss play a very important role to guarantee such application in terms of quality. In such environment, Quality of Service (QoS) is considered to be the most important network performance parameter which has a significant effect on multimedia applications like Voice Over Internet Protocol (VoIP) and others. internet protocol IPv6 was designed to improve QoS supported by internet protocol IPv4 and to enhance the reliability of packet based network to handle such services. This paper considered three queuing systems which are First In First Out (FIFO), Priority Queuing (PQ) and Weighted Fair Queuing (WFQ) as a comparative study to investigate their effects on real-time applications in IPv4 and IPv6 networks support. The proposed simulation environment was executed by Optimized Network Engineering Tools (OPNET) Modeler 14.5 where the simulation results are collected and analyzed. The results show that IPv6 with PQ provides better performance for real-time applications, despite that IPv6 with WFQ is more efficient with low priority traffic.

Modular design of a factor-graph-based inference engine on a System-On-Chip (SoC)

Factor graphs are probabilistic graphical frameworks for modeling complex and dynamic systems. They can be used in a broad range of application domains, from machine learning and robotics, to signal processing and digital communications. One important aspect that makes a factor graph very useful and very promising to be applied widely is its inference mechanism that is suitable for performing a complex model-based reasoning. However, its features have not fully explored and factor graphs are still used mainly as modeling tools that run on standard computers. Whereas in real applications such as robotics, one needs a practical implementation of such a framework. In this paper, we describe the development of a factor-graph-based inference engine that runs on a System-on-Chip (SoC). Running natively on a low level hardware, our factor graph engine delivers highest performance for real-time applications. We designed the embedded architecture so that it conveys important aspects such as modularity, scalability, flexibility and platform-friendly framework. The proposed architecture has customizable levels of parallelism as well as re-configurable modules that are extensible to accommodate large networks. We optimized the design to achieve high efficiency in terms of clock latency and resources consumption. We have tested our design on Xilinx Zynq-7000 SoCs and the implementation result demonstrates that the proposed framework can potentially be extended into a massively distributed probabilistic computing engine.

Simultaneous determination of ascorbic acid, dopamine and uric acid by a novel electrochemical sensor based on N2/Ar RF plasma assisted graphene nanosheets/graphene nanoribbons

A novel nitrogen/argon (N2/Ar) radio frequency (RF) plasma functionalized graphene nanosheet/graphene nanoribbon (GS/GNR) hybrid material (N2/Ar/GS/GNR) was developed for simultaneous determination of ascorbic acid (AA), dopamine (DA) and uric acid (UA). Various nitrogen mites introduced into GS/GNR hybrid structure was evidenced by a detailed microscopic, spectroscopic and surface area analysis. Owing to the unique structure and properties originating from the enhanced surface area, nitrogen functional groups and defects introduced on both the basal and edges, N2/Ar/GS/GNR/GCE showed high electrocatalytic activity for the electrochemical oxidations of AA, DA, and UA with the respective lowest detection limits of 5.3, 2.5 and 5.7 nM and peak-to-peak separation potential (ΔEP) (vs Ag/AgCl) in DPV of 220, 152 and 372 mV for AA/DA, DA/UA and AA/UA respectively. Moreover, the selectivity, stability, repeatability and excellent performance in real time application of the fabricated N2/Ar/GS/GNR/GCE electrode suggests that it can be considered as a potential electrode material for simultaneous detection of AA, DA, and UA.

Computation Offloading Strategy Based on Joint Allocation in Mobile Device Cloud

The contradiction between mobile terminal limited energy and users’ high requirements is more and more intensified, to provide satisfactory computation performance for real time applications, offloading workloads to Mobile Device Cloud (MDC) will be adopted. In this paper, we consider the problem of communication competition in the network, and put forward the offloading strategy based on the Joint Allocation Scheme (JAS) for lower latency. In the physical layer, the channel bandwidth allocation mode of OFDMA is used to make transmission rate realistic, combined with the task assignment, a delay model belongs to the NP problem can be established. We use the step-by-step solution, firstly consider the allocation of continuous task, and then use the simulated annealing algorithm (SAA) to get the optimal solution.

High voltage gain multiphase interleaved DC-DC converter for DC micro grid application using ıntelligent control

This paper presents Multiphase Interleaved Boost Converter (MIBC) with Voltage Multiplier Cell (VMC) supplied for DC micro grid application. The main focus of this research is to increase the voltage gain and reduce the voltage stress across the switch. The improvement in voltage gain is acheievd by recycling the stored energy in the inductor, VMC and voltage lift capacitor. In the proposed MIBC the input current is divided among the three converters. Hence, the rating of devices used in the converter can be reduced, which in turn minimises the ohmic loss of the switch. In addition, the interleaved converter decreases the voltage stress across the switch. The MIBC is compared with existing converters for various parameters such as voltage gain, voltage stress of the main switch and diode and the number of components used. The hardware is implemented for the propoosed MIBC to validate performance in real time application.

Optimal Spectrum Utilization and Flow Controlling In Heterogeneous Network with Reconfigurable Devices

AbstractFairness provisioning in heterogeneous networks is a prime issue for high-rate data flow, wherein the inter-connectivity property among different communication devices provides higher throughput. In Hetnet, optimal resource utilization is required for efficient resource usage. Proper resource allocation in such a network led to higher data flow performance for real-time applications. In view of optimal resource allocation, a resource utilization approach for a reconfigurable cognitive device with spectrum sensing capability is proposed in this paper. The allocation of the data flow rate at device level is proposed for optimization of network fairness in a heterogeneous network. A dynamic approach of rate-inference optimization is proposed to provide fairness in dynamic data traffic conditions. The simulation results validate the improvement in offered quality in comparison to multi-attribute optimization.

Coordinated Volt/VAr control for real-time operation of smart distribution grids

This paper proposes a new approach to the development of coordinated Volt/VAr control for real-time operation of smart distribution grids. The methodology intended for the coordinated Volt/VAr control conveys the minimization of the voltage violations and also a better distribution of the number of commutations among the control equipments. The control algorithm developed centrally coordinates the equipment actions in the conditions where the local control does not act properly. The adjustments are performed in the voltage regulator, in the capacitors banks and in the reactive power injected by the inverters of the distributed generation. The coordinated control strategy uses the fuzzy logic combined with a heuristic algorithm, which has implementation simplicity and suitable performance for real-time applications. A numerical example is presented aiming to clarify the procedure of the proposed control algorithm. Furthermore, the algorithm performance is verified through a modified IEEE 34 node test feeder under distinct operating conditions.

Energy Efficient Algorithms for Real-Time Traffic Over Fading Wireless Channels

This paper studies the problem of using minimum power to provide satisfactory performance for real-time applications over unreliable and fading wireless channels. We demonstrate that this problem can be formulated as a linear programming problem. However, this formulation involves exponentially many constraints, and many parameters are either unavailable or difficult to compute, which makes it infeasible to employ standard techniques to solve the linear programming problem. Instead, we propose a simple online algorithm for this problem. We prove that our algorithm provides satisfactory performance to all real-time applications, and the total power consumption can be made arbitrarily close to the theoretical lower bound. Furthermore, our algorithm has very low complexity and does not require knowledge of many parameters in the linear programming problem, including the distributions of channel qualities. We further extend our algorithm to address systems where real-time applications and non-real-time ones coexist. We demonstrate that our algorithm achieves both low total power consumption and high utility for each non-real-time client while satisfying the performance requirements of real-time clients. Simulation results further provide some insights in setting important parameters of our algorithms, and demonstrate that our algorithm indeed achieves a significant reduction in power consumption.

Exploiting Static Non-Uniform Cache Architectures for Hard Real-Time Computing

High-performance processors using Non-Uniform Cache Architecture (NUCA) are increasingly used to deal with the growing wire delays in multicore/manycore processors. Due to the convergence of high-performance computing with embedded computing, NUCA caches are expected to benefit high-end embedded systems as well. However, for real-time systems that use multicore processors with NUCA caches, it is crucial to bound worst-case execution time (WCET) accurately and safely. In this paper, we developed a WCET analysis approach by considering the effect of static NUCA caches on WCET. We compared the WCET in real-time applications with different topologies of static NUCA caches. Our experimental results demonstrated that the static NUCA cache could improve the worst-case performance of realtime applications using multicore processor compared to the cache with uniform access time.

TOWARDS AUTOMATED REGRESSION ANALYSIS AND MANAGEMENT THROUGHOUT SOFTWARE LIFE-CYCLE

Software application performance tends to degrade over a period of time due to introduction of new features, feature enhancements and bugs-fixes as part of the software maintenance lifecycle. Critical applications cannot afford the performance degradation. However, teams engaged in software maintenance are not too effective in detecting potential performance impacting issues during the test and release phases of the software engineering process, since the run-time environments for individual customers are difficult to simulate. This challenge is exacerbated for applications with a large installed-base. This research paper proposes the concept of Application Baselining as a means to effectively detecting and containing software regression. It provides indication of real-time application performance by monitoring its critical parameters over long periods of time. By keeping track of the changes made to the application and its environment, their impact on application performance is correlated. The changes which adversely impact the application performance are then rolled-back to mitigate their effect. Early work towards development of such a framework is presented.

Comparison between Open CV and MATLAB Performance in Real Time Applications

Comparison between Open CV and MATLAB Performance in Real Time Applications