Network Interface Research Articles

Implementasi Sistem Monitoring Jaringan Menggunakan Zabbix Berbasis SNMP

Network administrators require network monitoring in managing a network. Technological developments allow network monitoring using the SNMP protocol combined with a monitoring system using Zabbix. This research is designed for viewing and using routers to display information about the web. The problem that often occurs is the lack of administrators and the network monitoring system has not been accommodated. With this research, objectives continue to be developed, so that network administrators are helped and more quickly solve problems by monitoring existing networks. This study uses Zabbix as an open-source monitoring system. This application can display information from network devices such as Traffic Data, Bandwith Usage, and Network Interface. The results of the trials that have been carried out have proven to be able to monitor networks using SNMP-based Zabbix by displaying the expected results. This is indicated by the running of the monitoring system on the Zabbix application. It is hoped that by developing a network monitoring system using Zabbix-server, it will be easier to help speed up problems that occur and become a benchmark for the system being developed.

Intrabody Molecular Communication via Blood-Tissue Barrier for Internet of Bio-Nano Things

Molecular communication (MC) is an emerging communication paradigm that allows bio-nanomachines (NMs) to communicate using biochemical molecules as information carriers. It can be used in many promising biomedical applications such as the Internet of Bio-Nano Things (IoBNT) for targeted drug delivery and healthcare applications. In particular, the blood-tissue barrier (BTB) inside the body forms the main communication pathway for molecular information exchange between the NMs as well as between the intrabody nanonetwork and the bio-cyber interface in the IoBNT network. However, overcoming this barrier by the molecules is one of the main challenges for MC in the body. Therefore, spatiotemporal modeling of MC across the BTB is of particular interest. In this article, we develop a mathematical model and stochastic particle-based simulator for MC over high spatiotemporal resolution between mobile NMs in the blood capillary and the surrounding tissue. The transmitting bio-NM is modeled as a moving sphere with a continuous emission pattern over a specific duration. In this work, the blood capillary characteristics, including the BTB and blood flow, are modeled and their effect is examined on the molecular received signal. In addition, we examined the impact of the emission duration, the elimination rate, and the separation distance on the molecular received signal. The numerical results are verified using the developed particle-based simulator. This work can help in the optimum design and development of the IoBNT systems based on MC for biomedical applications, such as smart drug delivery and health monitoring systems.

Performance evaluation of modified mesh-based NoC architecture

With the advancement of technology in the field of VLSI, it is possible to integrate several computing elements onto a single chip. The performance of these single bus-based models still suffers from scalability on large-scale platforms. Therefore, network-on-chip (NoC) architecture integrating multiple cores in a single chip has emerged as an alternative. An efficient mapping is one of the most essential activities in high-performance multi-processor architectures. This research paper proposes an efficient core mapping and modified 2-D mesh NoC architecture. Every core is connected to the two routers via a network interface. In an efficient core mapping algorithm, the mapping region is selected based on Core Efficient Region (CER), which can improve the processor performance. The proposed core mapping algorithm is applied to the multimedia benchmarks. The experimental results show that the efficient core mapping algorithm outperforms the communication energy and performance when compared with other recent mapping algorithms.

An Analysis of MPTCP Congestion Control

Many devices contain more than one network interface. There is scope for multi-path transfer to utilise these network interfaces simultaneously. Multi-path TCP (MPTCP) is designed to provide improved resilience and resource utilisation through multi-path transfer. One of the key goals of MPTCP is to preserve fair resource sharing with regular TCP at network bottlenecks. Although the coupled congestion control algorithms can achieve this goal by coupling subflow congestion windows, the algorithms always assume that the subflow paths will share a bottleneck. As a consequence, MPTCP is unable to maximise throughput over all available paths at a non-shared bottleneck. We present a survey about MPTCP and its coupled congestion control algorithms. We then show that MPTCP coupled congestion control algorithms perform poorly when paths are disjoint and/or do not have similar delay and/or bandwidth characteristics.

MODULE HIGH-EFFICIENCY MULTIPROCESSOR SYSTEM WITH MULTIDIMENSIONAL AGGREGATING OF CHANNELS OF NETWORK INTERFACE

Context. In modern terms problem of constructing of the multiprocessor systems the special value acquires the base of standard popular technologies and components. It is caused by that such systems became popular and cheap vehicle platforms for highperformance calculations. In addition, practice pulls out problems complete decision of which in most cases possibly only due to application of high-performance calculations. Consequently, a theme of constructing of the cluster multiprocessor systems for today is actual, interesting and is on the stage of the active development. At the same time, the new high-quality stage of development of the multiprocessor cluster systems lies in area of the use of new modern network technologies. Presently the problem of choice and analysis of network technologies for the module multiprocessor cluster systems did not get due development, as well as problem of reorganization of structure ofnetwork interfaceby aggregating of channels of network interface.
 Objective. An aim is in-process put improvement of structure and increase of the productivity of the multiprocessor computer system by the multidimensional aggregating of channels of network interface, adapted to the decision of tasks of the investigated class.
 Method. The task of increase of efficiency of the module multiprocessor computer system is decided due to multidimensional aggregating of channels of network interface. Offered approach allowed not only to promote efficiency of parallelization but also substantially to decrease time of calculations. Such results succeeded to be attained due to diminishing to time of border exchange of data between the calculable knots of the cluster system.
 Results. A feature offered approach is that he allowed to realize a direct exchange data between main memory of knots of the multiprocessor system, that promotes the fast-acting of calculations and provides high-speed access to memory of her slave -nodes. Thus during an exchange by data between the knots of the system the system CPU gets unloaded and loading of channel which passes between the knots of the computer system goes down, that assists diminishing of time of border exchange of data between the calculable knots of the system.
 Conclusions. The results of the conducted experiments showed that the worked out multiprocessor system was used for creation of new technological processes. So, she is used in a fluidizer intensification of the сфероидизируещего annealing of long-length steelwork. Directly the technological process of heat treatment of metal acquires such advantages, as a high yield, substantial mionectic energy consumption and allows to carry out control of technological parameters in the modes of unisothermal treatment of metal.

Research on University Financial Accounting Management System Based on Big Data and Blockchain Data Fusion

The majority of traditional finance management in colleges and universities is manual. This backward management mode brings a lot of inconvenience to financial processing. An essential concern in the daily financial administration of colleges and universities is how to efficiently gather, handle, and evaluate this important financial information and apply this beneficial knowledge to the daily management of colleges and universities. College and university finance administration has become increasingly complex due to the rapid growth of these institutions. The standard financial accounting management system is far from adequate for the daily needs of colleges and universities as their size grows. As a result, a new financial accounting management system for universities is being developed based on the combination of big data and blockchain data. The embedded processor, DDR2 memory chip, network interface, and USB interface are all designed by the hardware section. The software element examines the needs of university financial accounting management before designing a model based on big data and blockchain integration for university financial accounting management. Finally, the financial accounting management function module and database are designed and tested. The experimental results show that the designed financial accounting management system can effectively carry out financial management, has good performance, and has certain application value.

Congestion aware low power on chip protocols with network on chip with cloud security

This article is to analyze the bottleneck problems of NoC in many more applications like multi-processor communication, computer architectures, and network interface processors. This paper aims to research the advantages and disadvantages of low congestion protocols on highway environments like multiple master multiple slave interconnections. A long-term evolution and effective on-chip connectivity solution for secured, congestion aware and low power architecture is emerged for Network-on-Chip (NoC) for MCSoC. Applications running simultaneously on a different chip are often exchanged dynamically on the chip network. Of-course, in general on chip communication, resources mean that applications may interact with shared resources to influence each other's time characteristics.

New network interface selection based on MADM and multi-objective whale optimization algorithm in heterogeneous wireless networks

New network interface selection based on MADM and multi-objective whale optimization algorithm in heterogeneous wireless networks

Evaluation of the Contribution Rates of Different Phases on Pavement Performance of Cement-Casting Asphalt Mixture

Cement-casting asphalt mixture (CCAM) exhibits excellent antirutting properties and has been widely used to address the severe rutting distress across the world. However, CCAM’s failure mechanism has not been comprehensively understood. To this end, the contribution rates of porous asphalt mixture (PAM), cementitious network, and asphalt-cement interface phases to CCAM’s pavement performance are evaluated. A novel method was developed to fabricate the cementitious network with the aid of plastic balls. Abrasion loss, strength, peak force, and fracture energy of PAM, cement samples, and CCAM samples are obtained through different tests. Analysis results show that the contribution rate of cementitious network to Cantabro loss is around 60% and that of the interface phase is around 30%. Interface phase and PAM phase approximately contribute 90% to the overall strength and fracture energy of CCAM. With the increase of polymer contents in asphalt binder, the contribution rate of PAM phase increases and the contribution rate of interface decreases. Contribution rates results together with samples’ fracture surface observation verify that the interaction between asphalt skeleton and cement network plays a vital role during CCAM’s failure process. Attention should be given to the physical-chemical interactions between asphalt and cement in the future study.

Разработка программного обеспечения электропривода для группового управления в электромеханической системе

Background. To operate multi-coordinate electromechanical systems require control of electric drives coordinated in time and space along each of the axes, which is called coordinated control. Thus, various computing tools and mathematical algorithms are used. They establish the baseline of the software for microprocessor control systems. At the same time, the implementation of control algorithms is limited by the computing resources of the hardware parts of control systems, including the limitations of the tools of information transmission. To consider and eliminate these limitations and thus, to improve operation of the multi-coordinate electromechanical system, the aim of the article is to update control algorithms and balance distribution of computational resources of electric drives control systems. Materials and methods. Data are presented on the software development for coordinated control of several electric drives as a part of an electromechanical system that performs coordinated motion along its axes in time and space. To synchronize the control, the following technical solutions have been applied: description of the path of the high-level controller in the form of a sequence of reference points, buffering the coordinates when received by the electric drives and subsequent interpolation. Balanced distribution of resources between the high-level controller and local systems of electric drives is carried out considering the intensity of data exchange via the network interface. When calculating the reference points by the high-level controller, approximation of the paths by line segments at time intervals of variable duration is carried out to describe the generic path within the allowable mismatch. Results. The algorithm to synchronize the system time of the electric drives and the high-level controller has been implemented to synchronize the interpolation of paths. To implement this algorithm and transfer the coordinates of reference points to electric drives, special commands are used. They have different priority levels depending on the required speed of execution. In accordance with this algorithm, software has been developed as an element of the microprocessor control system of the electric drive. Conclusions. Application of various technical tools and computational algorithms that make it possible to allocate the computing resources of the control system and rationally use them contributes to efficiency improvement, in particular, the consistency and timeliness of electric drives control as a part of multi-axis electromechanical systems. The authors have proved the efficiency of the approach of coordinated control with the use of buffering coordinates of reference points followed by interpolation of the paths depending on the system time of each of the electric drives.

A Deep Neural Network Interface Potential for Li‐Cu Systems

AbstractCopper foil is one of the most commonly used current collector materials in Li metal batteries. However, many problems on the Li–Cu interface have not been effectively solved due to the lack of a fundamental understanding of Li–Cu interaction at the atomic scale. In this work, a deep neural network interface potential for Li‐Cu systems using neural networks combined with active learning strategies is developed. The potential shows excellent performances on the energy and force calculations, physical properties predictions, and structure explorations. Moreover, the study of the Li adsorption behaviors on the Cu surface demonstrates the accuracy of this potential in the investigation of the Li–Cu interface. This potential for the Li‐Cu systems provides an important opportunity to advance the understanding of interface problems in Li metal batteries.

Application of embedded Linux in the design of Internet of Things gateway

AbstractTo study the development trend of embedded platforms in home appliances Internet of Things (IoT), an application of embedded Linux in the design of IoT gateway is designed. ARM microprocessor S3C2410, EM310 radio frequency (RF) module, and Ethernet DM9000A module are used to realize the home network information-processing platform. The platform utilizes existing network facilities, RF modules, and network interface modules to realize the interconnection of the home perception network through wireless or wired links. For experimental analysis, Ping the central server (gateway) from the IoT node B is set to twice: The first time ttl = 255 time = 1.9 ms, the second time: ttl = 255 time = 2.4 ms. After application verification, the system has the characteristics of low cost, small size, low power consumption, and vital ease of use. It can not only integrate the home Internet and the IoT gateway but also directly run application-layer communication protocols such as HTTP/MQTT between IoT nodes and Internet terminals. The design supports multi-hop communication and significantly increases the deployment range of IoT nodes without signal relay equipment, hence reducing the cost of IoT networking and the complexity of the network architecture.

OPERAnet, a multimodal activity recognition dataset acquired from radio frequency and vision-based sensors

This paper presents a comprehensive dataset intended to evaluate passive Human Activity Recognition (HAR) and localization techniques with measurements obtained from synchronized Radio-Frequency (RF) devices and vision-based sensors. The dataset consists of RF data including Channel State Information (CSI) extracted from a WiFi Network Interface Card (NIC), Passive WiFi Radar (PWR) built upon a Software Defined Radio (SDR) platform, and Ultra-Wideband (UWB) signals acquired via commercial off-the-shelf hardware. It also consists of vision/Infra-red based data acquired from Kinect sensors. Approximately 8 hours of annotated measurements are provided, which are collected across two rooms from 6 participants performing 6 daily activities. This dataset can be exploited to advance WiFi and vision-based HAR, for example, using pattern recognition, skeletal representation, deep learning algorithms or other novel approaches to accurately recognize human activities. Furthermore, it can potentially be used to passively track a human in an indoor environment. Such datasets are key tools required for the development of new algorithms and methods in the context of smart homes, elderly care, and surveillance applications.

Completely Independent Spanning Trees on BCCC Data Center Networks With an Application to Fault-Tolerant Routing

A set of <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> spanning trees in a graph <inline-formula><tex-math notation="LaTeX">$G$</tex-math></inline-formula> are called completely independent spanning trees (CISTs for short) if the paths joining every pair of vertices <inline-formula><tex-math notation="LaTeX">$x$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$y$</tex-math></inline-formula> in any two trees have neither vertex nor edge in common, except for <inline-formula><tex-math notation="LaTeX">$x$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$y$</tex-math></inline-formula> . The existence of multiple CISTs in the underlying graph of a network has applications in fault-tolerant broadcasting and secure message distribution. In this paper, we investigate the construction of CISTs in a server-centric data center network called BCube connected crossbars (BCCC), which can provide good network performance using inexpensive commodity off-the-shelf switches and commodity servers with only two network interface card (NIC) ports. The significant advantages of BCCC are its good expandability, lower communication latency, and higher robustness in component failure. Based on the structure of compound graphs of BCCC, we provide efficient algorithms to construct <inline-formula><tex-math notation="LaTeX">$\lceil \frac{n}{4}\rceil$</tex-math></inline-formula> CISTs in the logical graph of BCCC, denoted by <inline-formula><tex-math notation="LaTeX">$L$</tex-math></inline-formula> - <inline-formula><tex-math notation="LaTeX">$BCCC(n,k)$</tex-math></inline-formula> , for <inline-formula><tex-math notation="LaTeX">$n\geqslant 5$</tex-math></inline-formula> . As a by-product, we obtain a fault-tolerant routing that takes the constructed CISTs as its routing table. We then evaluate the performance of the fault-tolerant routing through simulation results.

Local Defogging Algorithm for Improving Visual Impact in Image Based on Multiobjective Optimization

The preprocessing of images is required for many applications based on industry, social, and academic requirements. Researchers have developed a number of techniques to improve the visual effect of images and appropriately interpret visual effects. The accuracy of visuals is important in cyber security, military organization, police organizations, and forensics to detect the true story from the pictures. They search for evidence by digging deep into the network in search of evidence. If visuals are not clear, preprocessing of images is not done correctly, then it may lead to wrong interpretations. This paper proposes an image local defogging technique based on multiobjective optimization to improve the visual effect of the image as well as the information entropy. The multiobjective function is selected to establish the image reconstruction model based on multiple objectives. The model is utilized to reconstruct a single image to moderate the impact of noise and other interference factors in the original image. The color constancy model and effective detail intensity model are also devised for image enhancement to get the visual details. The atmospheric light value and transmittance are evaluated using a physical model of atmospheric scattering, and the guided filter is used to maximize the transmittance of a single image and improve the efficiency of image defogging. The dark channel priority method is used to realize the local defogging of a single image and to design the local defogging algorithm. Experiments verify the optimization effect of the proposed algorithm in terms of information entropy and container network interface (CNI) value. The tone restoration degree is good, and it improves the overall image quality. The image defogging effect of the proposed algorithm is verified with respect to subjective and objective levels to check the efficacy of the proposed multiobjective model.

DASH Streaming traffic influence over energy efficient ethernet to improve energy savings

Dynamic Streaming over HTTP (DASH) is the main standard used in online video streaming services, given that more than 1.2 billion pay subscribers around the world use this standard. This fact entails billions of streaming connections between video servers and client displays. These devices involved in the streaming connection use an Ethernet Interface Card that consumes energy. In order to reduce the energy consumption, IEEE proposed the 802.3az Energy Efficient Ethernet standard, with a mechanism to make the network card change to a low power consumption mode when it is not in transmission mode. This behavior will be beneficial for services where traffic is sent in bursts, for instance video packet bursts like in video streaming over Real Time Transport Protocol in IPTV or the widely used DASH standard. Therefore, in this study the Ethernet traffic pattern when transmitting online video content using DASH is characterized in order to analyze the efficiency of the IEEE 802.3az standard under this video streaming scenario, and to verify the convenience of activating this energy saving alternative at the network interface of billions of client devices. The experiments have been conducted using a test-bed consisting of a full DASH streaming architecture, comparing different video segment sizes and changing the available bandwidth during the experiments in different scenarios in order to analyze the effect of the DASH content segment size on the Ethernet traffic pattern to identify the trade-off between energy efficiency, the energy savings, and the impact on the performance of the dynamic adaptation on the video streaming and reproduction.

A Real-Time Hardware Intrusion Detection System and a Classifying Features Algorithm

Nowadays, everybody needs to secure his/her activities. Existing levels of cyber-criminals need technology for detecting malicious activity. This work proposes a real-time Hardware IDS implemented on FPGA and an algorithm for classifying features from network traffic through the network interface card (NIC). It minimizes search time for extracting statistical features from connection records stored in connection queues to memory references. Therefore, it can detect most internal and external network attacks. A decision tree classifier is used as an inference engine and gives a high detection rate of 99.93%.

HXDP

The network interface cards (NICs) of modern computers are changing to adapt to faster data rates and to help with the scaling issues of general-purpose CPU technologies. Among the ongoing innovations, the inclusion of programmable accelerators on the NIC's data path is particularly interesting, since it provides the opportunity to offload some of the CPU's network packet processing tasks to the accelerator. Given the strict latency constraints of packet processing tasks, accelerators are often implemented leveraging platforms such as Field-Programmable Gate Arrays (FPGAs). FPGAs can be re-programmed after deployment, to adapt to changing application requirements, and can achieve both high throughput and low latency when implementing packet processing tasks. However, they have limited resources that may need to be shared among diverse applications, and programming them is difficult and requires hardware design expertise. We present hXDP, a solution to run on FPGAs software packet processing tasks described with the eBPF technology and targeting the Linux's eXpress Data Path. hXDP uses only a fraction of the available FPGA resources, while matching the performance of high-end CPUs. The iterative execution model of eBPF is not a good fit for FPGA accelerators. Nonetheless, we show that many of the instructions of an eBPF program can be compressed, parallelized, or completely removed, when targeting a purpose-built FPGA design, thereby significantly improving performance. We implement hXDP on an FPGA NIC and evaluate it running real-world unmodified eBPF programs. Our implementation runs at 156.25MHz and uses about 15% of the FPGA resources. Despite these modest requirements, it can run dynamically loaded programs, achieves the packet processing throughput of a high-end CPU core, and provides a 10X lower packet forwarding latency.

Cloud-Based Architecture for YOLOv3 Object Detector using gRPC and Protobuf

The deep learning-based object detector accuracy has surpassed conventional detection methods. Although implementation is still limited to hardware capabilities, this problem can be overcome by combining edge devices with cloud computing. The recent study of cloud-based object detector architecture is generally based on representational state transfer (RESTful web services), which uses a pooling system method for data exchange. As a result, this system leads to a low detection speed and cannot support real-time data streaming. Therefore, this study aims to enhance the detection speed in cloud-based object recognition systems using gRPC and Protobuf to support real-time detection. The proposed architecture was deployed on the Virtual Machine Instance (VMI) equipped with a Graphics Processing Unit (GPU). The gRPC server and YOLOv3 deep learning object detector were executed on the cloud server to handle detection requests from edge devices. Furthermore, the captured images from the edge devices were encoded into Protobuf format to reduce the message size delivered to the cloud server. The results showed that the proposed architecture improved detection speed performance on the client-side in the range of 0.27 FPS to 1.72 FPS compared to the state-of-the-art method. It was also observed that it could support multiple edge devices connection with slight performance degradation in the range of 1.78 FPS to 1.83 FPS, depending on the network interface used.

Involvement of White Matter Language Tracts in Glioma: Clinical Implications, Operative Management, and Functional Recovery After Injury.

To achieve optimal survival and quality of life outcomes in patients with glioma, the extent of tumor resection must be maximized without causing injury to eloquent structures. Preservation of language function is of particular importance to patients and requires careful mapping to reveal the locations of cortical language hubs and their structural and functional connections. Within this language network, accurate mapping of eloquent white matter tracts is critical, given the high risk of permanent neurological impairment if they are injured during surgery. In this review, we start by describing the clinical implications of gliomas involving white matter language tracts. Next, we highlight the advantages and limitations of methods commonly used to identify these tracts during surgery including structural imaging techniques, functional imaging, non-invasive stimulation, and finally, awake craniotomy. We provide a rationale for combining these complementary techniques as part of a multimodal mapping paradigm to optimize postoperative language outcomes. Next, we review local and long-range adaptations that take place as the language network undergoes remodeling after tumor growth and surgical resection. We discuss the probable cellular mechanisms underlying this plasticity with emphasis on the white matter, which until recently was thought to have a limited role in adults. Finally, we provide an overview of emerging developments in targeting the glioma-neuronal network interface to achieve better disease control and promote recovery after injury.