Asymmetric Paths Research Articles

BBR-based and fairness-guaranteed congestion control and packet scheduling for MPQUIC over heterogeneous networks

Multipath QUIC (MPQUIC) enables concurrent transmission over multiple paths, making it attractive to enhance the delivery performance of smartphones with multiple interfaces. Nevertheless, several issues in the current MPQUIC specification remain inadequately addressed. Congestion control in MPQUIC primarily relies on packet loss and favors paths with lower drop rates, which results in significant throughput degradation, especially in heterogeneous wireless networks with frequent random packet loss and varying path characteristics. Additionally, network fairness principles limits its performance, even in scenarios with independent and non-shared bottleneck paths. A final issue is that packet scheduling in dynamic and asymmetric paths poses a significant challenge, potentially causing out-of-order (OFO) arrivals and Head-of-Line (HoL) blocking if not appropriately managed. Inspired by Google’s BBR algorithm, this paper introduces a novel scheme called Shared Bottleneck and BBR-based Congestion Control (S2B2C) to address the above issues. It identifies subsets of subflows that share common bottlenecks within the MPQUIC connection based on the BBR’s internal mechanism. The scheme dynamically adjusts the pacing rate of these subflows to enhance goodput while preserving fairness with legacy single-path flows. Then, to mitigate inter-stream and intra-stream HoL blocking caused by OFO arrivals over asymmetric paths, we present a fine-grained Stream-path-bounded Priority-based Packet Scheduler (S2PS), which includes a stream dependency tree, a priority-based queuing, and a packet scheduling algorithm that uses a mixed-integer program formulation. Experimental results show that S2B2C achieves higher throughput while maintaining bottleneck fairness, and S2PS effectively mitigates HoL blocking with fewer OFO arrivals and shorter flow completion time compared to existing MPQUIC schemes in heterogeneous networks.

A Cooperative Scheduling Based on Deep Reinforcement Learning for Multi-Agricultural Machines in Emergencies

Effective scheduling of multiple agricultural machines in emergencies can reduce crop losses to a great extent. In this paper, cooperative scheduling based on deep reinforcement learning for multi-agricultural machines with deadlines is designed to minimize makespan. With the asymmetric transfer paths among farmlands, the problem of agricultural machinery scheduling under emergencies is modeled as an asymmetric multiple traveling salesman problem with time windows (AMTSPTW). With the popular encoder-decoder structure, heterogeneous feature fusion attention is designed in the encoder to integrate time windows and asymmetric transfer paths for more comprehensive and better feature extraction. Meanwhile, a path segmentation mask mechanism in the decoder is proposed to divide solutions efficiently by adding virtual depots to assign work to each agricultural machinery. Experimental results show that our proposal outperforms existing modified baselines for the studied problem. Especially, the measurements of computation ratio and makespan are improved by 26.7% and 21.9% on average, respectively. The computation time of our proposed strategy has a significant improvement over these comparisons. Meanwhile, our strategy has a better generalization for larger problems.

Asymmetric Sulfur Redox Paths in Sulfide-Based All-Solid-State Lithium–Sulfur Batteries

Asymmetric Sulfur Redox Paths in Sulfide-Based All-Solid-State Lithium–Sulfur Batteries

Analysis and simulation of the effect of large optical range difference of common path coherent-dispersion spectrometer on the detection of exoplanet radial velocities

The Exoplanet Explorer common-path coherent-dispersion spectrometer (CODES) utilizes a unique combination of an asymmetric common path Sagnac interferometer and a low to medium resolution spectrometer. The ideal optical range difference (OPD) interval for CODES is OPD ∈ {15.06 mm, 19.45 mm}; however, the OPD of CODES is 64.3 mm to achieve better detection accuracy. Though they will increase the accuracy of detection, large OPDs outside of the ideal interval will also reduce the contrast of the interference fringes, making phase changes more hazy. This may also significantly affect the radial velocity inversion and reduce CODES's instrumental accuracy. This study creates an inverse tone mapping operator based on the photographic model and designs an inverse tone mapping algorithm called CODESCE. The outcomes of the experiments demonstrate that the tone mapping algorithm CODESCE in this work is appropriate for enhancing the contrast of interference fringe images with high OPD, and it can enhance the contrast of interference fringes by three orders of magnitude when OPD = 64.3 mm; the processed interference fringes are located in the range of interference fringe curves of the optimal OPD. By comparison with other current approaches, the suggested algorithm yields superior processing outcomes.

Packets distribution over asymmetric paths using concurrent multipath transfer

AbstractConcurrent multipath transfer (CMT) is a transport layer protocol used for transferring data over multiple paths concurrently. In the case of asymmetric paths, the dissimilarity of delay, bandwidth, and loss rate among paths leads to challenges such as out‐of‐order packets, receiver buffer blocking, and throughput reduction. A framework that uses the end‐to‐end delay of paths to distribute the packets over asymmetric paths in ordering policy is proposed. The proposed framework detects network congestion in the assigned path and reduces the congestion window. Furthermore, the proposed framework predicts receiver buffer blocking and deactivates the highest delay path that causes this problem. The simulation results show that the proposed framework achieves highest throughput, lower entropy and lower average application end‐to‐end delay than the previous algorithms.

Laboratory X-ray Microscopy of 3D Nanostructures in the Hard X-ray Regime Enabled by a Combination of Multilayer X-ray Optics.

High-resolution imaging of buried metal interconnect structures in advanced microelectronic products with full-field X-ray microscopy is demonstrated in the hard X-ray regime, i.e., at photon energies > 10 keV. The combination of two multilayer optics-a side-by-side Montel (or nested Kirkpatrick-Baez) condenser optic and a high aspect-ratio multilayer Laue lens-results in an asymmetric optical path in the transmission X-ray microscope. This optics arrangement allows the imaging of 3D nanostructures in opaque objects at a photon energy of 24.2 keV (In-Kα X-ray line). Using a Siemens star test pattern with a minimal feature size of 150 nm, it was proven that features < 150 nm can be resolved. In-Kα radiation is generated from a Ga-In alloy target using a laboratory X-ray source that employs the liquid-metal-jet technology. Since the penetration depth of X-rays into the samples is significantly larger compared to 8 keV photons used in state-of-the-art laboratory X-ray microscopes (Cu-Kα radiation), 3D-nanopattered materials and structures can be imaged nondestructively in mm to cm thick samples. This means that destructive de-processing, thinning or cross-sectioning of the samples are not needed for the visualization of interconnect structures in microelectronic products manufactured using advanced packaging technologies. The application of laboratory transmission X-ray microscopy in the hard X-ray regime is demonstrated for Cu/Cu6Sn5/Cu microbump interconnects fabricated using solid-liquid interdiffusion (SLID) bonding.

Self-weight and thermal bifurcation analysis of functionally graded vertical annular plates

The present paper thoroughly investigates the influence of structural weight on the thermal buckling of standing circular and annular plates. The structure is composed of symmetrically functionally graded materials (FGM) in terms of its thickness. The first-order theory of shear deformation along with nonlinear strain–displacement equations has been employed to derive the governing equations of the FG plate. First, the asymmetric pre-buckling path of the structure under the influence of weight and heat is calculated by a semi-analytical method. The plate's stability relations are extracted using the adjacent equilibrium criterion and virtual work principle. Then, the stability equations are analyzed by the 2D generalized differential quadrature (GDQ) method. Parametric results are presented based on the analysis of the FGM power-law index, geometric ratios, and edge constraints on the buckling of the vertical plate. The study reveals the critical power-law index and thickness at which the structure becomes unstable, shedding light on the previously neglected calculation of weight-induced buckling in vertical structures. Also, the effect of weight on the buckling mode shapes of heavy plates and disturbing its symmetry is demonstrated. Additionally, this study presents the first investigation into the effect of weight on the thermal stability of annular FG plates.

A novel tool path smoothing algorithm of 6R manipulator considering pose-dependent dynamics by designing asymmetrical FIR filters

The joint dynamic constraints of robot manipulators are normally set to conservative constant values to meet the dynamic tolerances at different poses, which leads to incomplete utilization of the joint drive capability. To fully utilize the drive capability of joint drives, this paper proposes an asymmetrical finite impulse response (FIR) filter-based tool path smoothing algorithm, which considers the pose-dependent dynamics of the robot with 6 rotational (6R) joints. To analyze the pose-dependent motor drive capabilities, a simplified dynamics model is established by considering both the tangential and joint dynamic constraints. An asymmetrical FIR filter-based tool path smoothing algorithm is also proposed to realize different constraints of the acceleration and the deceleration limits at different positions of the linear segments. The tool tip position and the tool orientation commands are respectively smoothed in the Cartesian coordinate system and spherical coordinate system, with the constraints of the tool path deviations in the task frame. The synchronization of the position and the orientation is realized by adjusting the parameters of FIR filters. The simulation and experimental results show that the proposed algorithm guarantees the corner error tolerances of the tool tip position and the tool orientation. Moreover, the proposed method improves the robot motion efficiency by more than 10 % through the full utilization of the joint drive capability compared with the traditional tool path smoothing algorithm based on symmetrical FIR filters.

Generative adversarial networks based skin lesion segmentation

Skin cancer is a serious condition that requires accurate diagnosis and treatment. One way to assist clinicians in this task is using computer-aided diagnosis tools that automatically segment skin lesions from dermoscopic images. We propose a novel adversarial learning-based framework called Efficient-GAN (EGAN) that uses an unsupervised generative network to generate accurate lesion masks. It consists of a generator module with a top-down squeeze excitation-based compound scaled path, an asymmetric lateral connection-based bottom-up path, and a discriminator module that distinguishes between original and synthetic masks. A morphology-based smoothing loss is also implemented to encourage the network to create smooth semantic boundaries of lesions. The framework is evaluated on the International Skin Imaging Collaboration Lesion Dataset. It outperforms the current state-of-the-art skin lesion segmentation approaches with a Dice coefficient, Jaccard similarity, and accuracy of 90.1%, 83.6%, and 94.5%, respectively. We also design a lightweight segmentation framework called Mobile-GAN (MGAN) that achieves comparable performance as EGAN but with an order of magnitude lower number of training parameters, thus resulting in faster inference times for low compute resource settings.

Unraveling the Asymmetric O─O Radical Coupling Mechanism on Ru─O─Co for Enhanced Acidic Water Oxidation.

Heterogeneous oxides with multiple interfaces provide significant advantages in electrocatalytic activity and stability. However, controlling the local structure of these oxides is challenging. In this work, unique heterojunctions are demonstrated based on two oxide types, which are formed via pyrolysis of a ruthenocene metal-organic framework (Ru-MOF) at specific temperatures. The resulted Ru-MOF-400 exhibits excellent electrocatalytic activity, with an overpotential of 190mV at a current density of 10mA cm-2 in 0.1m HClO4 , and a mass activity of 2557 A gRu -1 , three orders of magnitude higher than commercial RuO2 . The Ru─O─Co bond formed by the incorporation of Co into the rutile lattice of RuO2 inhibits the disolution of Ru. Operando electrochemical investigations and density functional theory results reveal that the Ru-MOF-400 undergo asymmetric dual-active site oxide path mechanism during the acidic oxygen evolution reaction process, which is predominantly mediated by the asymmetric Ru─Co dual active site present at the interfaces between Co3 O4 and CoRuOx .

Image Desnowing via Deep Invertible Separation

Images taken on snowy days often suffer from severe negative visual effects caused by snowflakes. The task of removing snowflakes from a snowy image is known as image desnowing, which is challenging as image details are easily mistakenly treated and thus may be significantly lost during snowflake removal. Leveraging invertible neural networks (INNs), this paper presents a deep learning-based method for single image desnowing, which can remove snowflakes accurately while preserving image details well. Interpreting desnowing as an image decomposition problem, we propose an INN composed of two asymmetric interactive paths for predicting a latent image and a snowflake layer respectively. Such an INN is able to progressively refine the features of both latent images and snowflake layers for disentanglement, while retaining all information possibly relevant to latent image reconstruction. In addition, an attentive coupling layer supervised by snowflake masks is introduced to enhance feature dismantlement and a coupling-in-coupling structure is developed for further improvement. Extensive experiments show that, the proposed method outperforms existing ones on three benchmark datasets of synthetic and real-world images, and meanwhile it also shows advantages in terms of model size and computational efficiency.

A reliable alternating multi‐path transmission control protocol scheduling for bandwidth aggregation performance

SummaryThe Multi‐Path Transmission Control Protocol is a new generation protocol for the transport layer which allows multihomed devices to exploit simultaneously their own interfaces. This feature would normally lead to some high‐performance achievement in regard to regular TCP. However, the heterogeneous paths might cause the occurrence of the 'out‐of‐order' problem which requires the intervention of a more efficient scheduler to reach a high level of global bandwidth utilization. Since scheduling plays a key role in performance improvements, several studies have been implemented exploiting this idea, namely those that adopt the reactive approach and those others adopting the proactive one. In this paper, our goal is to improve the multipath throughput. The testbed experimentation consists primarily in the evaluation and analysis of the behaviour of different recent scheduling approaches with an asymmetric paths topology. Then, we propose an alternating scheduling approach which shed the light on bandwidth utilization. The results show that this approach is a more efficient solution than taking the reactive and proactive ones separately as it is based on a preliminary study that we conducted on the main performance and reliability parameters and has been implemented in the asymmetric multipath networks. This technique has led to a smart scheduling that provides a high level of throughput aggregation.

Looking for asymmetries between credit and output in the BRICS countries

This article aims to investigate the role of household domestic credit on GDP in the BRICS countries, controlling for other variables, such as inflation, government spending, GFCF, and interest rate. The econometric methodology involves the estimation of Nonlinear Autoregressive Distributed Lag (NARDL) models with Bounds Testing Approach to Cointegration, for quarterly data ranging from 2008Q3 to 2019Q4. The estimations indicate that household domestic credit and GDP, together with the control variables, have a common long-run path (cointegrate) in each country analyzed. But the long-run coefficients show that only in Brazil, Russia and China increases in household credit lead to a growth in output. As for short-run perturbations, it takes approximately two quarters, on average, for such shock to dissipate and the long-run equilibrium level to be restored. The asymmetric adjustment paths show a positive asymmetric case in Brazil and South Africa, but a negative asymmetry in Russia and India. For the Chinese case, the adjustment is symmetric. The evidence from Toda and Yamamoto’s Granger Causality tests between GDP and household domestic credit reveals China is the only case of bicausality. South Africa shows no sign of Granger-causality, while Brazil shows that household credit Granger-causes GDP, but not the opposite. In the case of Russia, GDP Granger-causes household domestic credit.

Overview of Common-Mode Noise Suppression Techniques: From Reflection to Absorption

Today’s fast-growing wireless communication technology has greatly increased the demand for the transmission of high-quality signals with high data rates. Because of its intrinsic advantages of high immunity to external noise, lower electromagnetic interference, harmonic suppression, and better linearity, differential signaling is preferable to single-ended signaling for many applications, including high-speed digital circuits, RF systems, and integrated circuits based on CMOS technology <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> , <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref> , <xref ref-type="bibr" rid="ref4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[4]</xref> . However, in real-world circuit applications, differential signals are usually accompanied by destructive common-mode (CM) noise, which may be induced by asymmetric differential transmission paths with bending or length mismatch. On the other hand, imbalance of the differential signal channels, including amplitude swings and differences between rising and falling times, could also contribute to CM noise. In addition, the radiation emission caused by CM noise is much stronger than the differential signals, leading to a reduced system reliability <xref ref-type="bibr" rid="ref5" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[5]</xref> . Therefore, CM suppression has been an inevitable challenge for differential circuits and systems.

Understanding Inherent Implication of Thermal Resistance in Double-Side Cooling Module

The double-side cooling (DSC) packaging becomes more and more popular with the great demands of high power and fast speed, especially for silicon carbide metal oxide semiconductor field effect transistors. Measurements and modeling of thermal resistance are critical for thermal management of DSC module. However, the thermal resistance of DSC module is still unclear due to the asymmetric dual thermal paths. In this article, a clear understanding of thermal resistance of DSC module measured by transient dual-interface method (TDIM) is explained. The thermal impedance of DSC module is analyzed through time- and frequency-domain response of the DSC thermal model. The cooling conditions in TDIM have no influence on the measured thermal resistance of DSC module. The measured thermal resistance from junction to top case (or bottom case) is half of the actual value. The important conclusions are verified by transient simulations and experiments. Based on the results, a new definition of thermal resistance of DSC module is proposed for exact evaluation of thermal resistance and reliability.

Effect of Path QoS on Throughput Aggregation Capability of the MPT Network Layer Multipath Communication Library

An increase in the use of smart and portable devices like smartphones, laptops, and tablets has led to a rise in the number of network interfaces and thus the number of possible channels for communication. However, the current approach over the Internet only employs a single path for a communication session. As an innovative and promising method for real-time transmission based on GRE-in-UDP encapsulation, which provides an IPv4 or IPv6 tunneling mechanism, this paper presents multipath throughput testing for the MPT network layer multipath communication library. We investigated the effectiveness of MPT's channel capacity aggregation while dealing with wired channels and examined scenarios in symmetric and asymmetric paths. Our network throughput measurements showed that MPT can efficiently aggregate the capacities of both symmetric and asymmetric paths. In this paper, we established a network topology that included a server, which we used for generating various quality of service (QoS) metrics. We measured how latency, transmission speed, packet loss rate, jitter, and the setting of the path weights influence throughput aggregation capability of the MPT communication library.

Modelling a Learning-Based Dynamic Tree Routing Model for Wireless Mesh Access Networks

Link asymmetry in wireless mesh access networks (WMAN) of Mobile ad-hoc Networks (MANETs) is due mesh routers’ transmission range. It is depicted as significant research challenges that pose during the design of network protocol in wireless networks. Based on the extensive review, it is noted that the substantial link percentage is symmetric, i.e., many links are unidirectional. It is identified that the synchronous acknowledgement reliability is higher than the asynchronous message. Therefore, the process of establishing bidirectional link quality through asynchronous beacons underrates the link reliability of asymmetric links. It paves the way to exploit an investigation on asymmetric links to enhance network functions through link estimation. Here, a novel Learning-based Dynamic Tree routing (LDTR) model is proposed to improve network performance and delay. For the evaluation of delay measures, asymmetric link, interference, probability of transmission failure is evaluated. The proportion of energy consumed is used for monitoring energy conditions based on the total energy capacity. This learning model is a productive way for resolving the routing issues over the network model during uncertainty. The asymmetric path is chosen to achieve exploitation and exploration iteratively. The learning-based Dynamic Tree routing model is utilized to resolve the multi-objective routing problem. Here, the simulation is done with MATLAB 2020a simulation environment and path with energy-efficiency and lesser E2E delay is evaluated and compared with existing approaches like the Dyna-Q-network model (DQN), asymmetric MAC model (AMAC), and cooperative asymmetric MAC model (CAMAC) model. The simulation outcomes demonstrate that the anticipated LDTR model attains superior network performance compared to others. The average energy consumption is 250 J, packet energy consumption is 6.5 J, PRR is 50 bits/sec, 95% PDR, average delay percentage is 20%.

${l}\,^2$-MPTCP: A Learning-Driven Latency-Aware Multipath Transport Scheme for Industrial Internet Applications

With various industrial wireless networks greeting booming development, modern industrial devices configured with several network interfaces increasingly become the norm. Such multihomed industrial devices can increase application throughput by making use of multiple network paths, enabled by the multipath transmission control protocol (MTCP) (MPTCP). However, MPTCP might be challenged in the heterogeneous industrial networks because concurrent transmitting industrial application data over asymmetric network paths with different delays is almost bound to the receive buffer blocking problem, which is caused by out-of-order packet arrival and is harmful to the performance of the multipath transmission. The existing MPTCP solutions generally use static mathematical models to evaluate path quality and prohibit transmission on paths with poor quality, which are unable to perform efficiently under highly dynamic and complex network environments. Therefore, in this article, we propose a learning-driven latency-aware MPTCP variant, called <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${l}\,^2$</tex-math></inline-formula> -MPTCP, which seeks to possibly mitigate the out-of-order packet arrival and receive buffer blocking problems associated with the network heterogeneity in the industrial Internet. <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${l}\,^2$</tex-math></inline-formula> -MPTCP accurately computes each MPTCP path’s forward delay and assigns application data to multiple paths according to their calculated forward delay differences by using a novel multiexpert learning-enabled forward delay estimator. <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${l}\,^2$</tex-math></inline-formula> -MPTCP dynamically manages path usage and chooses the optimal path collection for bandwidth aggregation and multipath transmission by using a promising reinforcement learning-empowered multipath manager. Experimental results demonstrate that <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${l}\,^2$</tex-math></inline-formula> -MPTCP outperforms the current MPTCP solutions in terms of multipathing service quality.

A Three-Stage Amplifier With Cascode Miller Compensation and Buffered Asymmetric Dual Path for Driving Large Capacitive Loads

In this brief, we combine a buffered asymmetric dual-path structure with cascode Miller compensation to extend the unity-gain bandwidth of a three-stage amplifier while decreasing its power consumption. This design is implemented in a 65 nm CMOS technology with 0.0017 mm2 chip area and 6.62 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\mu }\text{W}$ </tex-math></inline-formula> power consumption. Post-simulation results achieve <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${&gt;}100$ </tex-math></inline-formula> dB DC gain, 1.20 MHz UGB, and 0.391 V/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\mu }\text{s}$ </tex-math></inline-formula> SR with a 1.5 nF load capacitor.

Research on Path Planning in 3D Complex Environments Based on Improved Ant Colony Algorithm

Aiming at the problems of complex space, long planning time, and insufficient path security of 3D path planning, an improved ant colony algorithm (TGACO) is proposed, which can be used to solve symmetric and asymmetric path planning problems. Firstly, the 3D array is used to access the environment information, which can record the flight environment and avoid the inefficiency of planning. Secondly, a multi-objective function of distance and angle is established to improve the efficiency and safety of the path. Then, a target-guided heuristic function is proposed, and an anti-deadlock mechanism is introduced to improve the efficiency of the ant colony algorithm. Next, the node pheromone update rules are improved to further improve the efficiency of the algorithm. Finally, experiments prove the effectiveness of the improved algorithm, TGACO, and its efficiency in complex environments has obvious advantages. In the 20×20×20 environment, compared with the ant colony algorithm (ACO), the improved algorithm (TGACO) in this paper improves the path length, total turning angle, and running time by 17.8%, 78.4%, and 95.3%, respectively.