Low Latency TOE with Double-Queue Structure for 10Gbps Ethernet on FPGA.

The TCP protocol is a connection-oriented and reliable transport layer communication protocol which is widely used in network communication. With the rapid development and popular application of data center networks, high-throughput, low-latency, and multi-session network data processing has become an immediate need for network devices. If only a traditional software protocol stack is used for processing, it will occupy a large amount of CPU resources and affect network performance. To address the above issues, this paper proposes a double-queue storage structure for a 10G TCP/IP hardware offload engine based on FPGA. Furthermore, a TOE reception transmission delay theoretical analysis model for interaction with the application layer is proposed, so that the TOE can dynamically select the transmission channel based on the interaction results. After board-level verification, the TOE supports 1024 TCP sessions with a reception rate of 9.5 Gbps and a minimum transmission latency of 600 ns. When the TCP packet payload length is 1024 bytes, the latency performance of TOE's double-queue storage structure improves by at least 55.3% compared to other hardware implementation approaches. When compared with software implementation approaches, the latency performance of TOE is only 3.2% of the software approaches.

Enhancing Industrial Communication with Ethernet/Internet Protocol: A Study and Analysis of Real-Time Cooperative Robot Communication and Automation via Transmission Control Protocol/Internet Protocol.

This study explores the important task of validating data exchange between a control box, a Programmable Logic Controller (PLC), and a robot in an industrial setting. To achieve this, we adopt a unique approach utilizing both a virtual PLC simulator and an actual PLC device. We introduce an innovative industrial communication module to facilitate the efficient collection and storage of data among these interconnected entities. The main aim of this inquiry is to examine the implementation of Ethernet/IP (EIP), a relatively new addition to the industrial network scenery. It was designed using ODVA's Common Industrial Protocol (CIP™). The Costumed real-time data communication module was programmed in C++ for the Linux Debian platform and elegantly demonstrates the impressive versatility of EIP as a means for effective data transfer in an industrial environment. The study's findings provide valuable insights into Ethernet/IP's functionalities and capabilities in industrial networks, bringing attention to its possible applications in industrial robotics. By connecting theoretical knowledge and practical implementation, this research makes a significant contribution to the continued development of industrial communication systems, ultimately improving the efficiency and effectiveness of automation processes.

Non-Stationary Characteristics of AQM Based on the Queue Length.

We performed a non-stationary analysis of a class of buffer management schemes for TCP/IP networks, in which the arriving packets were rejected randomly, with probability depending on the queue length. In particular, we derived formulas for the packet waiting time (queuing delay) and the intensity of packet losses as functions of time. These results allow us to observe how the evolution of the waiting time and losses depend on initial conditions (e.g., the full buffer) and system parameters (e.g., dropping probabilities, load, packet size distribution). As side results, the stationary waiting time and packet loss probability were obtained. Numerical examples demonstrate applicability of the theoretical results.

Optimizing Face Recognition Inference with a Collaborative Edge-Cloud Network.

The rapid development of deep-learning-based edge artificial intelligence applications and their data-driven nature has led to several research issues. One key issue is the collaboration of the edge and cloud to optimize such applications by increasing inference speed and reducing latency. Some researchers have focused on simulations that verify that a collaborative edge-cloud network would be optimal, but the real-world implementation is not considered. Most researchers focus on the accuracy of the detection and recognition algorithm but not the inference speed in actual deployment. Others have implemented such networks with minimal pressure on the cloud node, thus defeating the purpose of an edge-cloud collaboration. In this study, we propose a method to increase inference speed and reduce latency by implementing a real-time face recognition system in which all face detection tasks are handled on the edge device and by forwarding cropped face images that are significantly smaller than the whole video frame, while face recognition tasks are processed at the cloud. In this system, both devices communicate using the TCP/IP protocol of wireless communication. Our experiment is executed using a Jetson Nano GPU board and a PC as the cloud. This framework is studied in terms of the frame-per-second (FPS) rate. We further compare our framework using two scenarios in which face detection and recognition tasks are deployed on the (1) edge and (2) cloud. The experimental results show that combining the edge and cloud is an effective way to accelerate the inferencing process because the maximum FPS achieved by the edge-cloud deployment was 1.91× more than the cloud deployment and 8.5× more than the edge deployment.

Impact of the Dropping Function on Clustering of Packet Losses.

The dropping function mechanism is known to improve the performance of TCP/IP networks by reducing queueing delays and desynchronizing flows. In this paper, we study yet another positive effect caused by this mechanism, i.e., the reduction in the clustering of packet losses, measured by the burst ratio. The main contribution consists of two new formulas for the burst ratio in systems with and without the dropping function, respectively. These formulas enable the easy calculation of the burst ratio for a general, non-Poisson traffic, and for an arbitrary form of the dropping function. Having the formulas, we provide several numerical examples that demonstrate their usability. In particular, we test the effect of the dropping function's shape on the burst ratio. Several shapes of the dropping function proposed in the literature are compared in this context. We also demonstrate, how the optimal shape can be found in a parameter-depended class of functions. Finally, we investigate the impact of different system parameters on the burst ratio, including the load of the system and the variance of the service time. The most important conclusion drawn from these examples is that it is not only the dropping function that reduces the burst ratio by far; simultaneously, the more variable the traffic, the more beneficial the application of the dropping function.

Diffusion Model of a Non-Integer Order PIγ Controller with TCP/UDP Streams.

In this article, a way to employ the diffusion approximation to model interplay between TCP and UDP flows is presented. In order to control traffic congestion, an environment of IP routers applying AQM (Active Queue Management) algorithms has been introduced. Furthermore, the impact of the fractional controller PIγ and its parameters on the transport protocols is investigated. The controller has been elaborated in accordance with the control theory. The TCP and UDP flows are transmitted simultaneously and are mutually independent. Only the TCP is controlled by the AQM algorithm. Our diffusion model allows a single TCP or UDP flow to start or end at any time, which distinguishes it from those previously described in the literature.

An Emergency Response System: Construction, Validation, and Experiments for Disaster Management in a Vehicular Environment.

Natural disasters and catastrophes not only cost the loss of human lives, but adversely affect the progress toward sustainable development of the country. As soon as disaster strikes, the first and foremost challenge for the concerned authorities is to make an expeditious response. Consequently, they need to be highly-organized, properly-trained, and sufficiently-equipped to effectively respond and limit the destructive effects of a disaster. In such circumstances, communication plays a vital role, whereby the consequences of tasks assigned to the workers for rescue and relief services may be streamlined by relaying necessary information among themselves. Moreover, most of the infrastructure is either severely damaged or completely destroyed in post-disaster scenarios; therefore, a Vehicular Ad Hoc Network (VANET) is used to carry out the rescue operation, as it does not require any pre-existing infrastructure. In this context, the current work proposes and validates an effective way to relay the crucial information through the development of an application and the deployment of an experimental TestBed in a vehicular environment. The TestBed may able to provide a way to design and validate the algorithms. It provides a number of vehicles with onboard units embedded with a credit-card-size microcomputer called Raspberry Pi and a Global Positioning System (GPS) module. Additionally, it dispatches one of the pre-defined codes of emergency messages based on the level of urgency through multiple hops to a central control room. Depending on the message code received from a client, the server takes appropriate action. Furthermore, the solution also provides a graphical interface that is easy to interpret and to understand at the control room to visualize the rescue operation on the fly.

Performance Evaluation of IEEE 802.11ah Networks With High-Throughput Bidirectional Traffic.

So far, existing sub-GHz wireless communication technologies focused on low-bandwidth, long-range communication with large numbers of constrained devices. Although these characteristics are fine for many Internet of Things (IoT) applications, more demanding application requirements could not be met and legacy Internet technologies such as Transmission Control Protocol/Internet Protocol (TCP/IP) could not be used. This has changed with the advent of the new IEEE 802.11ah Wi-Fi standard, which is much more suitable for reliable bidirectional communication and high-throughput applications over a wide area (up to 1 km). The standard offers great possibilities for network performance optimization through a number of physical- and link-layer configurable features. However, given that the optimal configuration parameters depend on traffic patterns, the standard does not dictate how to determine them. Such a large number of configuration options can lead to sub-optimal or even incorrect configurations. Therefore, we investigated how two key mechanisms, Restricted Access Window (RAW) grouping and Traffic Indication Map (TIM) segmentation, influence scalability, throughput, latency and energy efficiency in the presence of bidirectional TCP/IP traffic. We considered both high-throughput video streaming traffic and large-scale reliable sensing traffic and investigated TCP behavior in both scenarios when the link layer introduces long delays. This article presents the relations between attainable throughput per station and attainable number of stations, as well as the influence of RAW, TIM and TCP parameters on both. We found that up to 20 continuously streaming IP-cameras can be reliably connected via IEEE 802.11ah with a maximum average data rate of 160 kbps, whereas 10 IP-cameras can achieve average data rates of up to 255 kbps over 200 m. Up to 6960 stations transmitting every 60 s can be connected over 1 km with no lost packets. The presented results enable the fine tuning of RAW and TIM parameters for throughput-demanding reliable applications (i.e., video streaming, firmware updates) on one hand, and very dense low-throughput reliable networks with bidirectional traffic on the other hand.

Compression and Encryption of ECG Signal Using Wavelet and Chaotically Huffman Code in Telemedicine Application.

In mobile health care monitoring, compression is an essential tool for solving storage and transmission problems. The important issue is able to recover the original signal from the compressed signal. The main purpose of this paper is compressing the ECG signal with no loss of essential data and also encrypting the signal to keep it confidential from everyone, except for physicians. In this paper, mobile processors are used and there is no need for any computers to serve this purpose. After initial preprocessing such as removal of the baseline noise, Gaussian noise, peak detection and determination of heart rate, the ECG signal is compressed. In compression stage, after 3 steps of wavelet transform (db04), thresholding techniques are used. Then, Huffman coding with chaos for compression and encryption of the ECG signal are used. The compression rates of proposed algorithm is 97.72 %. Then, the ECG signals are sent to a telemedicine center to acquire specialist diagnosis by TCP/IP protocol.

The amino acid's backup bone - storage solutions for proteomics facilities.

Proteomics methods, especially high-throughput mass spectrometry analysis have been continually developed and improved over the years. The analysis of complex biological samples produces large volumes of raw data. Data storage and recovery management pose substantial challenges to biomedical or proteomic facilities regarding backup and archiving concepts as well as hardware requirements. In this article we describe differences between the terms backup and archive with regard to manual and automatic approaches. We also introduce different storage concepts and technologies from transportable media to professional solutions such as redundant array of independent disks (RAID) systems, network attached storages (NAS) and storage area network (SAN). Moreover, we present a software solution, which we developed for the purpose of long-term preservation of large mass spectrometry raw data files on an object storage device (OSD) archiving system. Finally, advantages, disadvantages, and experiences from routine operations of the presented concepts and technologies are evaluated and discussed. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

WebTag: Web browsing into sensor tags over NFC.

Information and Communication Technologies (ICTs) continue to overcome many of the challenges related to wireless sensor monitoring, such as for example the design of smarter embedded processors, the improvement of the network architectures, the development of efficient communication protocols or the maximization of the life cycle autonomy. This work tries to improve the communication link of the data transmission in wireless sensor monitoring. The upstream communication link is usually based on standard IP technologies, but the downstream side is always masked with the proprietary protocols used for the wireless link (like ZigBee, Bluetooth, RFID, etc.). This work presents a novel solution (WebTag) for a direct IP based access to a sensor tag over the Near Field Communication (NFC) technology for secure applications. WebTag allows a direct web access to the sensor tag by means of a standard web browser, it reads the sensor data, configures the sampling rate and implements IP based security policies. It is, definitely, a new step towards the evolution of the Internet of Things paradigm.

Interoperation of an UHF RFID reader and a TCP/IP device via wired and wireless links.

A main application in radio frequency identification (RFID) sensor networks is the function that processes real-time tag information after gathering the required data from multiple RFID tags. The component technologies that contain an RFID reader, called the interrogator, which has a tag chip, processors, coupling antenna, and a power management system have advanced significantly over the last decade. This paper presents a system implementation for interoperation between an UHF RFID reader and a TCP/IP device that is used as a gateway. The proposed system consists of an UHF RFID tag, an UHF RFID reader, an RF end-device, an RF coordinator, and a TCP/IP I/F. The UHF RFID reader, operating at 915 MHz, is compatible with EPC Class-0/Gen1, Class-1/Gen1 and 2, and ISO18000-6B. In particular, the UHF RFID reader can be combined with the RF end-device/coordinator for a ZigBee (IEEE 802.15.4) interface, which is a low-power wireless standard. The TCP/IP device communicates with the RFID reader via wired links. On the other hand, it is connected to the ZigBee end-device via wireless links. The web based test results show that the developed system can remotely recognize information of multiple tags through the interoperation between the RFID reader and the TCP/IP device.

[International communication system of acupuncture-moxibustion based on OSI model].

Borrowing the open system interconnection (OSI) model of internet protocol and the 5W theory in communication studies, the links in the international communication of acupuncture-moxibustion can be classified into seven layers: physical layer, data link layer, network layer, transport layer, session layer, presentation layer and application layer, therefore it is built an OSI model of international communication system of acupuncture-moxibustion. It is pointed out that present international communication system of acupuncture-moxibustion is similar to the user datagram protocol (UDP) in internet technology. Evidence-based medicine (EBM) plays a key role to modernize acupuncture- moxibustion theory based upon its clinical effects. According to phenomenon-taking by classified analogy, it is found that the PICO model of EBM agrees pretty well with the "three-way handshakes" mechanism of the internet transmission control protocol (TCP), which is promising to construct an international discourse of acupuncture-moxibustion compatible with western medicine. Thus it will benefit to explore the scientific connotation of acupuncture-moxibustion theory and significantly improve the international prestige of acupuncture-moxibustion.

Executing native Java code in R: an approach based on a local server.

The R language is widely used for data analysis. However, it does not allow for complex object-oriented implementation and it tends to be slower than other languages such as Java, C and C++. Consequently, it can be more computationally efficient to run native Java code in R. To do this, there exist at least two approaches. One is based on the Java Native Interface (JNI) and it has been successfully implemented in the rJava package. An alternative approach consists of running a local server in Java and linking it to an R environment through a socket connection. This alternative approach has been implemented in an R package called J4R. This article shows how this approach makes it possible to simplify the calls to Java methods and to integrate the R vectorization. The downside is a loss of performance. However, if the vectorization is used in conjunction with multithreading, this loss of performance can be compensated for.

Measurement system with real time data converter for conversion of I 2 S data stream to UDP protocol data.

A central goal of systems neuroscience is to simultaneously measure the activities of all achievable neurons in the brain at millisecond resolution in freely moving animals. This paper describes a protocol converter which is part of a measurement acquisition system for multichannel real time recording of brain signals. In practice, in such techniques, a primary consideration of reliability leads to great necessity towards increasing the sampling rate of these signals while simultaneously increasing the resolution of A/D conversion to 24 bits or even to the unprecedented 32 bits per sample. In fact, this was the guiding principle for our team in the present study. By increasing the temporal and amplitude resolution, it is supposed that we get enabled to discover or recognize and identify new signal components which have previously been masked at a "low" temporal and amplitude resolution, and these new signal components, in the future, are likely to contribute to a deeper understanding of the workings of the brain.

Real Time Processing and Transferring ECG Signal by a Mobile Phone.

The real-time ECG signal processing system based on mobile phones is very effective in identifying continuous ambulatory patients. It could monitor cardiovascular patients in their daily life and warns them in case of cardiac arrhythmia. An ECG signal of a patient is processed by a mobile phone with this proposed algorithm. An IIR low-pass filter is used to remove the noise and it has the 55 Hz cutoff frequency and order 3. The obtained SNR showed a desirable noise removal and it helps physicians in their diagnosis. In this paper, Hilbert transform was used and the R peaks are important component to differ normal beats from abnormal ones. The results of sensitivity and positive predictivity of algorithm are 96.97% and 95.63% respectively. If an arrhythmia occurred, 4 seconds of this signal is displayed on the mobile phone then it will be sent to a remote medical center by TCP/IP protocol.