Asynchronous Data Transmission Research Articles

ApSpGEMM: Accelerating Large-scale SpGEMM with Heterogeneous Collaboration and Adaptive Panel

The Sparse General Matrix-Matrix multiplication (SpGEMM) is a fundamental component for many applications, such as algebraic multigrid methods (AMG), graphic processing, and deep learning. However, the unbearable latency of computing high-dimensional, large-scale sparse matrix multiplication on GPUs hinders the development of these applications. An effective approach is heterogeneous cores collaborative computing, but this method must address three aspects: (1) irregular non-zero elements lead to load imbalance and irregular memory access, (2) different core computing latency differences reduce computational parallelism, and (3) temporary data transfer between different cores introduces additional latency overhead. In this work, we propose an innovative framework for collaborative large-scale sparse matrix multiplication on CPU-GPU heterogeneous cores, named ApSpGEMM. ApSpGEMM is based on sparsity rules and proposes reordering and splitting algorithms to eliminate the impact of non-zero element distribution features on load and memory access. Then adaptive panels allocation with affinity constraints among cores improves computational parallelism. Finally, carefully arranged asynchronous data transmission and computation balance communication overhead. Compared with state-of-the-art SpGEMM methods, our approach provides excellent absolute performance on matrices with different sparse structures. On heterogeneous cores, the GFlops of large-scale sparse matrix multiplication is improved by 2.25 to 7.21 times.

Development of an Intelligent Service Platform for a Poultry House Facility Environment Based on the Internet of Things

In recent years, the poultry breeding industry has been converted into a large-scale, intensive, and intelligent production mode. The Internet of Things (IoT) is under rapid development, which promotes the development of precision livestock farming. In this study, we developed an intelligent service platform for a facility environment based on the IoT structure, utilizing the capabilities of Platform as a Service (PaaS). The platform consists of four layers, including an information perception layer, network layer, management service layer, and application layer. By using the cloud service model with a distributed network architecture, asynchronous data transmission, and a distributed file system, the platform can centrally manage multiple farm’s data. The intelligent service platform includes the following functions: displaying environmental data, water and electricity consumption, data analysis, and managing production data. Over a 500-day trial period in a live poultry house, the platform demonstrated high data integrity (>87%) and resilience against network disruptions and power outages. The data validity of each environmental element exceeded 94%, among which the validity of the temperature, humidity, and carbon dioxide concentration exceeded 99%. The overall accuracy of the dataset remained relatively high, providing a robust data foundation for further research. Key features included audio analysis, environmental monitoring, and production data management. The platform’s operational status was efficiently communicated via data statistics and email alerts, facilitating timely system recovery. The demonstrated modules included sound recognition, psychrometric charts for visual alerts, and financial analysis tools, offering versatile solutions for integrating PLF models and advanced analytics.

Analyzing the blockchain mining strategy in Industrial Internet of Things: A game theoretical approach

Deploying Proof-of-Work (PoW) consensus based blockchain systems in Industrial Internet of Things (IIoT) scenarios that rely on wireless channels for data transmission faces new challenges. An IIoT device working in industrial production may participate in the operation of blockchain as a miner. These devices not only need to consume their own computation capability to compete for the right to generate blocks, but also need to transmit newly generated blocks to other devices through wireless channel to continuously maintain the global ledger. Asynchronous mining and data transmission by IIoT devices in wireless environments may significantly interfere with the propagation of blocks in the system and result the reduction of mining payoff, thereby affecting the willingness of IIoT devices to participate in maintaining blockchain system. This paper considers the behavior of independent mining between multiple IIoT devices as a non-cooperative game, which we call the Wireless Mining Game (WMG). Markov chain is adopted to derive the block propagation model under the wireless channel, and then the payoff model of IIoT device is formulated. IIoT devices can make reasonable mining decisions by evaluating the computation capability of other IIoT devices and the probability of successful block transmission. We analyze the Nash equilibrium of the WMG and the corresponding mining behavior set between two-players scenario through theoretical modeling and experiments. We also analyzed the expected mining payoff of the IIoT devices in the multiple devices scenario.

Broadcast speech recognition and control system based on Internet of Things sensors for smart cities

Abstract With the wide popularization of Internet of Things (IoT) technology, the design and implementation of intelligent speech equipment have attracted more and more researchers’ attention. Speech recognition is one of the core technologies to control intelligent mechanical equipment. An industrial IoT sensor-based broadcast speech recognition and control system is presented to address the issue of integrating a broadcast speech recognition and control system with an IoT sensor for smart cities. In this work, a design approach for creating an intelligent voice control system for the Robot operating system (ROS) is provided. The speech recognition control program for the ROS is created using the Baidu intelligent voice software development kit, and the experiment is run on a particular robot platform. ROS makes use of communication modules to implement network connections between various system modules, mostly via topic-based asynchronous data transmission. A point-to-point network structure serves as the communication channel for the many operations that make up the ROS. The hardware component is mostly made up of the main controller’s motor driving module, a power module, a WiFi module, a Bluetooth module, a laser ranging module, etc. According to the experimental findings, the control system can identify the gathered sound signals, translate them into control instructions, and then direct the robot platform to carry out the necessary actions in accordance with the control instructions. Over 95% of speech is recognized. The control system has a high recognition rate and is simple to use, which is what most industrial controls require. It has significant implications for the advancement of control technology and may significantly increase production and life efficiency.

Акустический способ передачи информации в устройстве горизонтального направленного бурения

An acoustic method has been developed for transmitting information about the coordinates of the drill head during the operation of a horizontal directional drilling device during the project laying of communications. The paper considers the traditional technology of horizontal directional drilling, and the electromagnetic method of transmitting information in trenchless laying of communications. An acoustic channel for information transmission has been studied in terms of asynchronous data transmission. The temporal structure of the signal, as well as the structure of the byte issued in acoustic transmission of information, have been developed. The optimal operating frequency of the transceiver system was chosen and the capacity of the acoustic information transmission channel was evaluated. The requirements for the modulator-demodulator of signals of an acoustic information transmission system are determined, the simulation of the propagation of an information package is carried out, taking into account the resonant properties of the converter using the Multisim circuit simulation package. For modeling, an equivalent circuit has been developed that forms an information package in the form of a chess code.

Application of Blockchain for Secure Data Transmission in Distributed State Estimation

The application of renewable energy sources in the power grid increases the necessity of tracking the system state, especially in smart grids, where there is a bidirectional transfer of data and power. The complexity of coupling between communication and the electrical infrastructure in a smart grid increases the risk of security breaches. Increasing the state estimation accuracy helps the smart grid operator efficiently manage the system. This article proposes an integration of distributed state estimation with a blockchain-designed communication platform. Additionally, the asynchronous data transmission, which is more likely to happen in the real world, is considered as the second task of this research. Finally, a detailed analysis of the blockchain-based application in distributed state estimation is provided. The numerical analysis shows that the proposed method meets real-world performance requirements and brings high security and reliability to the distributed state estimation process.

Influence of synchronous primary care telemedicine versus in-person visits on diabetes, hypertension, and hyperlipidemia outcomes: a systematic review

BackgroundTelemedicine can be used to manage various health conditions, but there is a need to investigate its effectiveness for chronic disease management in the primary care setting. This study compares the effect of synchronous telemedicine versus in-person primary care visits on patient clinical outcomes.MethodsA systematic review of studies published in PubMed and Web of Science between 1996 and January 2021 was performed using keywords related to telemedicine, diabetes, hypertension, and hyperlipidemia. Included studies compared synchronous telemedicine versus in-person visits with a primary care clinician, and examined outcomes of hemoglobin A1c (HbA1c), blood pressure, and/or lipid levels.ResultsOf 1724 citations screened, 7 publications met our inclusion criteria. Included studies were published between 2000 and 2018. Three studies were conducted in the United States, 2 in Spain, 1 in Sweden, and 1 in the United Kingdom. The telemedicine interventions investigated were multifaceted. All included synchronous visits with a primary care provider through videoconferencing and/or telephone, combined with other components such as asynchronous patient data transmission. Five studies reported on HbA1c changes, 5 on blood pressure changes, and 3 on changes in lipid levels. Compared to usual care with in-person visits, telemedicine was associated with greater reductions in HbA1c at 6 months and similar HbA1c outcomes at 12 months. Telemedicine conferred no significant differences in blood pressure and lipid levels compared to in-person clinic visits.ConclusionsA systematic review of the literature found few studies comparing clinical outcomes resulting from synchronous telemedicine versus in-person office visits, but the existing literature showed that in the primary care setting, telemedicine was not inferior to in-person visits for the management of diabetes, hypertension, or hypercholesterolemia. These results hold promise for continued use of telemedicine for chronic disease management.

HAP-aided two-way relaying for FSO access networks using optical CDMA

A free-space optical access network with multiple ground stations (GSs) connected by a high-altitude platform (HAP) is proposed. The HAP plays a role of a two-way relay node that supports all-optical amplify-and-forward and half-duplex transmission. In the network, optical code-division multiple-access is utilized to enable asynchronous and simultaneous data transmission among GSs. In further steps of the study, the mathematical expressions of two system metrics including bit-error rate (BER) and network throughput are derived. They consider many physical layer impairments, such as power loss, atmospheric turbulence, pointing error, multiple-access interference, and receiver noise. Eventually, numerical results of the system performance under consideration of the number of GSs, the bit rate, and the received power confirm the feasibility of the proposed system as well as provide useful information for network design.

W48. EFFICIENT HIPSC BASED DISEASE MODELLING USING CRISPR/CAS9

Experiments in high energy physics (HEP) operate at the forefront of detector technology, electronics, data acquisition (DAQ), data analysis, and computing. With the advent of high-energy accelerators running at large beam intensities, there is a great demand for radiation-hard high speed protocol for data transmission. Along with the detector data, communication signals like trigger, timing and control (TTC) information plays an important role. The TTC information needs to be transmitted over long distances using asynchronous communication links, which act as a bridge between the front-end radiation hard electronics and the DAQ. Maintaining the timing relationships and synchronization among payloads is an essential pre-requisite for the integrity of the acquired data. However, the phase relationship among the transmitted TTC signals gets disrupted due to the various sources of inter-signal interferences and channel link uncertainties. To address this challenge we have developed a phase alignment logic that can be applied over any asynchronous data-transmission protocol. We have implemented the proposed logic on the widely used radiation tolerant data-transmission protocol, called Gigabit Transceiver (GBT). The DAQ architecture needs to be resilient enough to avoid the loss of data or the errors in physics payload. The principal idea for implementation of the logic is to have an effective strategy to realign the synchronization without the need for power-on reset (PoR). The approach reduces the number of dead cycles that otherwise would have been utilized to minimize the timing errors. The chosen hardware for the experimental setup is 28 nm Stratix-V FPGA from Intel Inc. The benchmark of the system performance is illustrated in terms of the measurements of resource utilization, results of signal integrity, route delays, eye diagram and jitter analysis.

An Asynchronous Data Transmission Method in Heterogeneous Wireless Networks

With the massive deployment and application of intelligent systems such as smart life, smart medical care, and smart transportation, it is becoming more common for heterogeneous wireless networks such as WiFi, Zigbee, and Bluetooth to coexist in the same physical space. To improve the communication efficiency under the coexistence of heterogeneous wireless networks, this paper proposes an asynchronous data transmission method based on CTC technology, which constantly monitors the sleep and wake-up cycles of heterogeneous devices, makes full use of the wake-up cycle of the receiving terminal, and uses asynchronous methods to achieve cross-technology transmission of data packets. We also give a specific implementation scheme and use the program to simulate the transmission effect. The results show that our proposed method effectively reduces data transmission time and balances channel transmission throughput.

Development of FPGA based phase alignment logic for the high speed protocol in HEP Experiments

Experiments in high energy physics (HEP) operate at the forefront of detector technology, electronics, data acquisition (DAQ), data analysis, and computing. With the advent of high-energy accelerators running at large beam intensities, there is a great demand for radiation-hard high speed protocol for data transmission. Along with the detector data, communication signals like trigger, timing and control (TTC) information plays an important role. The TTC information needs to be transmitted over long distances using asynchronous communication links, which act as a bridge between the front-end radiation hard electronics and the DAQ. Maintaining the timing relationships and synchronization among payloads is an essential pre-requisite for the integrity of the acquired data. However, the phase relationship among the transmitted TTC signals gets disrupted due to the various sources of inter-signal interferences and channel link uncertainties. To address this challenge we have developed a phase alignment logic that can be applied over any asynchronous data-transmission protocol. We have implemented the proposed logic on the widely used radiation tolerant data-transmission protocol, called Gigabit Transceiver (GBT). The DAQ architecture needs to be resilient enough to avoid the loss of data or the errors in physics payload. The principal idea for implementation of the logic is to have an effective strategy to realign the synchronization without the need for power-on reset (PoR). The approach reduces the number of dead cycles that otherwise would have been utilized to minimize the timing errors. The chosen hardware for the experimental setup is 28 nm Stratix-V FPGA from Intel Inc. The benchmark of the system performance is illustrated in terms of the measurements of resource utilization, results of signal integrity, route delays, eye diagram and jitter analysis.

High-speed Parallel Feature Extraction Algorithm of Wind Tunnel Image Based on GPU

In wind tunnel test, the serial feature extraction algorithm of wind tunnel image based on CPU is too slow to meet the execution speed requirements of wind tunnel test. To solve this problem, a high-speed parallel feature extraction algorithm of wind tunnel image based on GPU is proposed. The proposed algorithm is optimized in parallel from the CUDA kernel level and CUDA stream level to speed up feature extraction execution. In image pre-processing, a pixel is processed by a CUDA thread to achieve parallelization. In feature extraction, the image segmentation is introduced to parallelize 8-connected boundary tracking algorithm. And a CUDA thread is used to process an image block to parallelize feature extraction process. Furthermore, the proposed algorithm uses CUDA stream to asynchronous data transmission and data processing to achieve CUDA stream level parallelism. To verify the efficiency and effectiveness of the GPU-based algorithm, comparative experiment between CPU and GPU is conducted. The experimental results show that the performance of GPU-based parallel algorithm is far better than that of CPU-based serial algorithm. The GPU-based parallel algorithm can greatly improve the execution speed of feature extraction while ensuring the accuracy of feature data.

Optoelectronic rotary connector for data transmission

Many technical solutions require the transmission of data between rotating parts. The article presents a data transmission solution based on an optoelectronic rotary connector. The optoelectronic connector is characterised by high speed of data transmission and long life of the mechanical components, with the choice of synchronous and asynchronous data transmission modes. Keywords: optoelectronic rotary connector, optical data transmission, detection of optical radiation

Load Distribution and Determination of Loss Probability in Asynchronous Network

In this paper, a general description of the problem of calculating probability–time characteristics was presented. At the initial stage of studying this problem, we studied the asynchronous data transmission of the constituent broadband digital network with the integration of services for both the channel switching subnetwork and the packet switching subnetwork. And also the circuit switching subnetwork was investigated using the bypass of the direction of transmission of the stream of multi-channel calls. At the same time, the source data of the problem of calculating probabilistic characteristics were set for the channel switching subnetwork, the characteristics that were determined during the solution of the problem were listed, and some assumptions were described that made it possible to adequately approximate the study of such a model to the functioning of a real network. Next, a mathematical model for calculating the loss probabilities was described, both for communication channels and for nodes of the channel switching subnetwork included in the asynchronous transfer mode network. The model of information traffic transmission is presented, where the method is implemented using network bypass directions. A method has been developed for generating a nodal load of a channel switching subnet and a system of equations has been obtained, the solution of which determines the value of a nodal load relative to the probability of loss on communication channels and proved the uniqueness of the solution of this system of equations.

A novel parallel finite element procedure for nonlinear dynamic problems using GPU and mixed-precision algorithm

Purpose The purpose of this paper is to improve the computational speed of solving nonlinear dynamics by using parallel methods and mixed-precision algorithm on graphic processing units (GPUs). The computational efficiency of traditional central processing units (CPUs)-based computer aided engineering software has been difficult to satisfy the needs of scientific research and practical engineering, especially for nonlinear dynamic problems. Besides, when calculations are performed on GPUs, double-precision operations are slower than single-precision operations. So this paper implemented mixed precision for nonlinear dynamic problem simulation using Belytschko-Tsay (BT) shell element on GPU. Design/methodology/approach To minimize data transfer between heterogeneous architectures, the parallel computation of the fully explicit finite element (FE) calculation is realized using a vectorized thread-level parallelism algorithm. An asynchronous data transmission strategy and a novel dependency relationship link-based method, for efficiently solving parallel explicit shell element equations, are used to improve the GPU utilization ratio. Finally, this paper implements mixed precision for nonlinear dynamic problems simulation using the BT shell element on a GPU and compare it to the CPU-based serially executed program and a GPU-based double-precision parallel computing program. Findings For a car body model containing approximately 5.3 million degrees of freedom, the computational speed is improved 25 times over CPU sequential computation, and approximately 10% over double-precision parallel computing method. The accuracy error of the mixed-precision computation is small and can satisfy the requirements of practical engineering problems. Originality/value This paper realized a novel FE parallel computing procedure for nonlinear dynamic problems using mixed-precision algorithm on CPU-GPU platform. Compared with the CPU serial program, the program implemented in this article obtains a 25 times acceleration ratio when calculating the model of 883,168 elements, which greatly improves the calculation speed for solving nonlinear dynamic problems.

Interference Analysis for Optical Wireless Communications in Network-on-Chip (NoC) Scenarios

Optical wireless (OW) communications, besides being of great interest for indoor and outdoor applications, have been recently proposed as a powerful alternative to the existing wired and wireless radio frequency (RF) interconnects in a network-on-chip (NoC). Design and analysis of networks with OW links require a careful investigation of cross-link interference, which impacts considerably the efficiency of systems that reuse the same channel for multiple transmissions. Yet, there is no comprehensive analysis of interference for OW NoCs, and the analyses of crosstalk in optical waveguide communications usually rely on synchronous data transmissions. A novel framework for the analysis of on-chip OW communications in the presence of cross-link cochannel interference and noise is proposed, where asynchronous data transmissions are considered. Self-beating of interfering signals is also considered, which was often neglected in previous literature. The bit error probability (BEP) for arbitrary number of interfering sources is derived as a function of signal-to-noise ratio (SNR), interference powers, detection threshold and pulse shaping, using both exact and approximation methods. The proposed analysis can be applied to both noise- and interference-limited cases, and enables a system designer to evaluate reuse distance between links that share the same optical carrier for simultaneous communication in NoCs.

Improving the performance of hybrid multiple access scheme in millimeter wave wireless personal area networks

IEEE 802.15.3c standard for millimeter wave (mmWave) wireless PAN (WPAN) specifies a hybrid medium access control (MAC) protocol consisting of contention based and contention free channel access schemes, with corresponding durations termed as contention access period (CAP) and channel time allocation period (CTAP). While CTAP is used for the transmission of isochronous data streams, CAP is used for the transmission of control messages such as channel time allocation (CTA) requests. In this paper, we propose an improvement for the hybrid MAC protocol specified by 802.15.3c, considering transmission of asynchronous data streams over the uplink from the devices (DEVs) to the pico net coordinator (PNC). The proposed scheme advocates transmission of asynchronous data frames during CAP as well as CTAP. The CTA requests which are normally transmitted during CAP would be piggybacked on the data frames. Using the theory of discrete time Markov chain (DTMC), we present an analytical model to evaluate the network throughput and average frame delay under the proposed scheme. The results establish that the proposed scheme improves the network throughput while reducing the average delay considerably. The analytical results are corroborated by extensive simulation studies.

On the Transmission of Asynchronous Data Streams Over Packet Switched Networks with Random Multiple Access

On the Transmission of Asynchronous Data Streams Over Packet Switched Networks with Random Multiple Access

One-Request Scheme for M2P Data Transmissions in Software-Defined IoT Networks

Software-defined networks (SDNs) have been utilized in applications of the Internet of Things (IoT), termed as software-defined IoT (SD-IoT) network, because of the popularity and capability of mobile devices being used for networking in relatively large areas. In an SD-IoT system, the sensing data are asynchronously harvested by the mobile sensing nodes and are also asynchronously uploaded to the gateways of an SDN. Thus, all the sensing data are asynchronously transmitted from the gateways to the data servers in the pattern of multipoints-to-point (M2P) data transmissions. Even if the sensing data are generated from the same sensing event, the controller of SDN has no knowledge about this relationship. Thus, such asynchronous M2P data transmissions from the same sensing event at the gateways will generate many redundant requests to their controller by OpenFlow protocol of SDN. In this paper, we investigate the redundant requests caused by the asynchronous M2P data transmissions in the SD-IoT network. We model the relationship between the sensing events and the uploading gateways by utilizing their spatial locations and the distribution of mobile sensor nodes. To reduce the loads on the controller for the asynchronous M2P data transmissions, we propose a one-request scheme for SD-IoT networks, to batch the forwarding rules of the multiple data transmissions from the same event by the first one request from a gateway. Furthermore, we discuss the conflict between the M2P data transmission and the potential sensing events and propose the routing scheme with multiple sensing events. Our extensional simulations verify the effectiveness of our proposed approach.

Cloud-based data management system for automatic real-time data acquisition from large-scale laying-hen farms

Management of poultry farms in China mostly relies on manual labor. Since such a large amount of valuable data for the production process either are saved incomplete or saved only as paper documents, making it very difficult for data retrieve, processing and analysis. An integrated cloud-based data management system (CDMS) was proposed in this study, in which the asynchronous data transmission, distributed file system, and wireless network technology were used for information collection, management and sharing in large-scale egg production. The cloud-based platform can provide information technology infrastructures for different farms. The CDMS can also allocate the computing resources and storage space based on demand. A real-time data acquisition software was developed, which allowed farm management staff to submit reports through website or smartphone, enabled digitization of production data. The use of asynchronous transfer in the system can avoid potential data loss during the transmission between farms and the remote cloud data center. All the valid historical data of poultry farms can be stored to the remote cloud data center, and then eliminates the need for large server clusters on the farms. Users with proper identification can access the online data portal of the system through a browser or an APP from anywhere worldwide. Keywords: cloud-based data management system (CDMS), egg production, intensified laying-hen farms, asynchronous data transmission, metadata DOI: 10.3965/j.ijabe.20160904.2488 Citation: Chen H Q, Xin H W, Teng G H, Meng C Y, Du X D, Mao T T, et al. Cloud-based data management system for automatic real-time data acquisition from large-scale laying-hen farms. Int J Agric & Biol Eng, 2016; 9(4): 106－115.