Network Interface Research Articles

Unsupervised KPIs-Based Clustering of Jobs in HPC Data Centers.

Performance analysis is an essential task in high-performance computing (HPC) systems, and it is applied for different purposes, such as anomaly detection, optimal resource allocation, and budget planning. HPC monitoring tasks generate a huge number of key performance indicators (KPIs) to supervise the status of the jobs running in these systems. KPIs give data about CPU usage, memory usage, network (interface) traffic, or other sensors that monitor the hardware. Analyzing this data, it is possible to obtain insightful information about running jobs, such as their characteristics, performance, and failures. The main contribution in this paper was to identify which metric/s (KPIs) is/are the most appropriate to identify/classify different types of jobs according to their behavior in the HPC system. With this aim, we had applied different clustering techniques (partition and hierarchical clustering algorithms) using a real dataset from the Galician computation center (CESGA). We concluded that (i) those metrics (KPIs) related to the network (interface) traffic monitoring provided the best cohesion and separation to cluster HPC jobs, and (ii) hierarchical clustering algorithms were the most suitable for this task. Our approach was validated using a different real dataset from the same HPC center.

Streaming Video Classification Using Machine Learning

This paper presents a method using neural networks and Markov Decision Process (MDP) to identify the source and class of video streaming services. The paper presents the design and implementation of an end-to-end pipeline for training and classifying a machine learning system that can take in packets collected over a network interface and classify the data stream as belonging to one of five streaming video services: You Tube, You Tube TV, Netflix, Amazon Prime, or HBO

An approach to creating wireless network interface amongst IPv4, IPv6 and dual stack networks

The networking community is colossally moving towards the IPv6 addressing abandoning the IPv4 address space. This occurs because of the enormous development of Internet utilization over the networks. Government has mandated from June 2006 onwards that all the devices would be IPv6 ready as the postponement in the organization of IPv6 would bring about the negative effect of future development and worldwide network. In this paper we are managing the effect of various interfaces like IPv4 just, IPv6 just and Dual stack instrument over remote systems with changing PHY and MAC layer interface with various wireless standards. The outcomes of results are simulated over Qualnet 5.1 test system with different parameters like throughput, delay, jitter and packet delivery ratio is been calculated.

An approach to creating wireless network interface amongst IPv4, IPv6 and dual stack networks

An approach to creating wireless network interface amongst IPv4, IPv6 and dual stack networks

Branched actin networks are assembled on microtubules by adenomatous polyposis coli for targeted membrane protrusion.

Cell migration is driven by pushing and pulling activities of the actin cytoskeleton, but migration directionality is largely controlled by microtubules. This function of microtubules is especially critical for neuron navigation. However, the underlying mechanisms are poorly understood. Here we show that branched actin filament networks, the main pushing machinery in cells, grow directly from microtubule tips toward the leading edge in growth cones of hippocampal neurons. Adenomatous polyposis coli (APC), a protein with both tumor suppressor and cytoskeletal functions, concentrates at the microtubule-branched network interface, whereas APC knockdown nearly eliminates branched actin in growth cones and prevents growth cone recovery after repellent-induced collapse. Conversely, encounters of dynamic APC-positive microtubule tips with the cell edge induce local actin-rich protrusions. Together, we reveal a novel mechanism of cell navigation involving APC-dependent assembly of branched actin networks on microtubule tips.

Ice-out and freshet fluxes of CO2 and CH4 across the air–water interface of the channel network of a great Arctic delta, the Mackenzie

Carbon dioxide (CO2) and methane (CH4) were monitored at five sites spanning the upstream–downstream extent of the Mackenzie Delta channel network during May 2010, capturing the historically under-sampled ice-out period that includes the rising freshet, peak water levels and the early falling freshet (flood recession). Unexpectedly, partial pressures of CO2 in the Mackenzie River were undersaturated during the rising freshet before water levels peaked, indicating net CO2 invasion at instantaneous CO2 flux rates (F-CO2) ranging from –112 to –258 mg-C m-2 d-1. Net CO2 invasion was also observed around the time of peak water levels at sites in the middle and outer delta. Following peak water levels, the Mackenzie River switched to saturation and net CO2 evasion (F-CO2 from 74 to 177 mg-C m-2 d-1). Although the Peel River (which flows into the west side of the Mackenzie Delta) was a strong emitter of CO2 (F-CO2 from 373 to 871 mg-C m-2 d-1), overall, the Mackenzie River and Delta were weak emitters of CO2 during the 2010 ice-out period. All sites were strong emitters of CH4 during ice-out, however, with the highest evasive fluxes observed in the outer delta when the extent of flooded delta landscape was greatest. Estimated aerial fluxes from Mackenzie Delta channel surfaces during May 2010 ranged from 2.1 to 4.8 Gg-C as CO2, and 186 to 433 Mg-C as CH4. These results provide critical information that can be used to refine gas flux estimates in high-latitude circumpolar river deltas during the relatively under-studied ice-out period.

Leveraging energy saving capabilities of current EEE interfaces via pre-coalescing

The low power idle mode implemented by Energy Efficient Ethernet (EEE) allows network interfaces to save up to 90% of their nominal energy consumption when idling. There is an ample body of research that recommends the use of frame coalescing algorithms—that enter the low power mode as soon as there is no more traffic waiting to be sent, and delay the exit from this mode until there is an acceptable amount of traffic queued—to minimize energy usage while maintaining an acceptable performance. However, EEE capable hardware from several manufactures delays the entrance to the low power mode for a considerable amount of time (hysteresis). In this paper we augment existing EEE energy models to account for the hysteresis delay and show that, using the configuration ranges provided by manufacturers, most existing EEE networking devices are unable to obtain significant energy savings. To improve their energy efficiency, we propose to implement frame coalescing directly at traffic sources, before reaching the network interface. We also derive the optimum coalescing parameters to obtain a given target energy consumption at the EEE device when its configuration parameters are known in advance.

Network Interface Architecture for Remote Indirect Memory Access (RIMA) in Datacenters

Remote Direct Memory Access (RDMA) fabrics such as InfiniBand and Converged Ethernet report latency shorter by a factor of 50 than TCP. As such, RDMA is a potential replacement for TCP in datacenters (DCs) running low-latency applications, such as Web search and memcached. InfiniBand’s Shared Receive Queues (SRQs), which use two-sided send/recv verbs (i.e., channel semantics ), reduce the amount of pre-allocated, pinned memory (despite optimizations such as InfiniBand’s on-demand paging (ODP)) for message buffers. However, SRQs are limited fundamentally to a single message size per queue, which incurs either memory wastage or significant programmer burden for typical DC traffic of an arbitrary number (level of burstiness) of messages of arbitrary size. We propose remote indirect memory access (RIMA) , which avoids these pitfalls by providing (1) network interface card (NIC) microarchitecture support for novel queue semantics and (2) a new “verb” called append . To append a sender’s message to a shared queue, the receiver NIC atomically increments the queue’s tail pointer by the incoming message’s size and places the message in the newly created space. As in traditional RDMA, the NIC is responsible for pointer lookup, address translation, and enforcing virtual memory protections. This indirection of specifying a queue (and not its tail pointer, which remains hidden from senders) handles the typical DC traffic of an arbitrary sender sending an arbitrary number of messages of arbitrary size. Because RIMA’s simple hardware adds only 1--2 ns to the multi-\mu s message latency, RIMA achieves the same message latency and throughput as InfiniBand SRQ with unlimited buffering. Running memcached traffic on a 30-node InfiniBand cluster, we show that at similar, low programmer effort, RIMA achieves significantly smaller memory footprint than SRQ. However, while SRQ can be crafted to minimize memory footprint by expending significant programming effort, RIMA provides those benefits with little programmer effort. For memcached traffic, a high-performance key-value cache ( FastKV ) using RIMA achieves either 3× lower 96 th-percentile latency or significantly better throughput or memory footprint than FastKV using RDMA.

Wi-ESP—A tool for CSI-based Device-Free Wi-Fi Sensing (DFWS)

AbstractRecent progress in Device-Free Wi-Fi Sensing (DFWS) has established the use of wireless signals like Wi-Fi not only to communicate but also as a tool to enable device-free sensing. As an emerging technique, DFWS has many capable applications such as sensing activity and gesture and fall detection, monitoring elderly, surveillance, and many more applications while waiving out the necessity to mount devices on the object. A wide range of applications can use the channel state information (CSI) from commercial Wi-Fi devices pervasively for ubiquitous sensing. Existing CSI tools, such as the Intel 5300 network interface controller tool or the Atheros 9390 tool, have limitations when deployed in large-scale systems due to their high deployment costs and limitations in the resolution of CSI measurements. Due to these shortcomings, DFWS applications need an alternative CSI tool in order to perform efficiently. In this paper, we present ESP32-based Wi-ESP as a CSI gathering tool that can report detailed CSI measurements based on 802.11n standards. The proposed Wi-ESP tool works as a complete device by collecting the CSI measurements as well as processing further for DFWS applications. Wi-ESP can work as standalone device, unlike other CSI tools, and can offer large-scale deployment to many DFWS applications. In this paper, we have explored the options of Wi-ESP as a tool for CSI measurements and processing and propose it as a tool for DFWS.

MyoMiner: explore gene co-expression in normal and pathological muscle

BackgroundHigh-throughput transcriptomics measures mRNA levels for thousands of genes in a biological sample. Most gene expression studies aim to identify genes that are differentially expressed between different biological conditions, such as between healthy and diseased states. However, these data can also be used to identify genes that are co-expressed within a biological condition. Gene co-expression is used in a guilt-by-association approach to prioritize candidate genes that could be involved in disease, and to gain insights into the functions of genes, protein relations, and signaling pathways. Most existing gene co-expression databases are generic, amalgamating data for a given organism regardless of tissue-type.MethodsTo study muscle-specific gene co-expression in both normal and pathological states, publicly available gene expression data were acquired for 2376 mouse and 2228 human striated muscle samples, and separated into 142 categories based on species (human or mouse), tissue origin, age, gender, anatomic part, and experimental condition. Co-expression values were calculated for each category to create the MyoMiner database.ResultsWithin each category, users can select a gene of interest, and the MyoMiner web interface will return all correlated genes. For each co-expressed gene pair, adjusted p-value and confidence intervals are provided as measures of expression correlation strength. A standardized expression-level scatterplot is available for every gene pair r-value. MyoMiner has two extra functions: (a) a network interface for creating a 2-shell correlation network, based either on the most highly correlated genes or from a list of genes provided by the user with the option to include linked genes from the database and (b) a comparison tool from which the users can test whether any two correlation coefficients from different conditions are significantly different.ConclusionsThese co-expression analyses will help investigators to delineate the tissue-, cell-, and pathology-specific elements of muscle protein interactions, cell signaling and gene regulation. Changes in co-expression between pathologic and healthy tissue may suggest new disease mechanisms and help define novel therapeutic targets. Thus, MyoMiner is a powerful muscle-specific database for the discovery of genes that are associated with related functions based on their co-expression.MyoMiner is freely available at https://www.sys-myo.com/myominer

Minimizing the usage of hardware counters for collective communication using triggered operations

Triggered operations and counting events or counters are building blocks used by communication libraries, such as MPI, to offload collective operations to the Host Fabric Interface (HFI) or Network Interface Card (NIC). Triggered operations can be used to schedule a network or arithmetic operation to occur in the future, when a trigger counter reaches a specified threshold. On completion of the operation, the value of a completion counter increases by one. With this mechanism, it is possible to create a chain of dependent operations, so that the execution of an operation is triggered when all the operations it depends on have completed its execution.Triggered operations rely on hardware counters on the HFI and are a limited resource. Thus, if the number of required counters exceeds the number of hardware counters, a collective needs to stall until a previous collective completes and counters are released. In addition, if the HFI has a counter cache, utilizing a large number of counters can cause cache thrashing and provide poor performance. Therefore, it is important to reduce the number of counters, especially when running on a large supercomputer or when an application uses non-blocking collectives and multiple collectives can run concurrently. Moreover, counters being a scarce resource, it is important for the MPI library to be able to estimate the number of counters required by a collective so that it can fallback to the software implementation when the number of available counters is less than the required number.In this paper, we propose an algorithm to optimize the number of hardware counters used when offloading collectives with triggered operations. With our algorithm, different operations can share and re-use trigger and completion counters based on the dependences among them and their topological orderings. We have also proposed models to estimate the number of counters required by different collectives when using the optimization algorithm. While the proposed counter optimization algorithm assumes that the dependences among various operations in a collective are represented using a Directed Acyclic Graph (DAG), there might be cases when no DAGs are provided for the collective. In this paper, we also discuss how we can optimize the usage of counters for such cases. Our experimental results show that our proposed algorithm significantly reduces the number of counters over a naïve approach that does not consider the dependences among the operations.

Electromagnetic compatibility issues in hybrid wired and wireless industrial networks.

Industrial networks are currently the only communication means designed for real-time systems used in industry. Networked control systems (NCS) are still important and commonly used type of such systems operating on shop floor. As a computerized node of NCS, a programmable logic controller (PLC) is usually used. In most cases, contemporary devices of such kind are equipped with more than one network interface of various types. Typically, only one interface is activated in NCS. Sometimes, the other is used for communication between NCS and supervisory systems. Occasionally, it is additionally involved in the data transmission in the factory IT systems. In general, however, using a single network interface is a more common solution. In this paper, the mutual utilization of more than one interface is discussed in order to back up the NCS network and to manage the node-related traffic within the scope of higher level services. The question of dependability of such a system from the electromagnetic compatibility point of view is discussed. The example is provided based on Profinet via wired and wireless connection.

An Analytical Hierarchy Process Combined with Game Theory for Interface Selection in 5G Heterogeneous Networks

Network convergence is considered as one of the key solutions to the problem of achieving future high-capacity and reliable communications. This approach overcomes the limitations of separate wireless technologies. Efficient interface selection is one of the most important issues in convergence networks. This paper solves the problem faced by users of selecting the most appropriate interface in the heterogeneous radio-access network (RAN) environment. Our proposed scheme combines a hierarchical evaluation of networks and game theory to solve the network-selection problem. Instead, of considering a fixed weight system while ranking the networks, the proposed scheme considers the service requirements, as well as static and dynamic network attributes. The best network is selected for a particular service request. To establish a hierarchy among the network-evaluation criteria for service requests, an analytical hierarchy process (AHP) is used. To determine the optimum network selection, the network hierarchy is combined with game theory. AHP attains the network hierarchy. The weights of different access networks for a service are calculated. It is performed by combining AHP scores considering user’s experienced static network attributes and dynamic radio parameters. This paper provides a strategic game. In this game, the network scores of service requests for various RANs and the user’s willingness to pay for these services are used to model a network-versus-user game. The Nash equilibria signify those access networks that are chosen by individual user and result maximum payoff. The examples for the interface selection illustrate the effectiveness of the proposed scheme.

In Situ-Generated Multivalent Aptamer Network for Efficient Capture and Sensitive Electrochemical Detection of Circulating Tumor Cells in Whole Blood.

Monitoring circulating tumor cells (CTCs) in human blood can offer useful information for convenient metastasis diagnosis, prognosis, and treatment of cancers. However, it remains a substantial challenge to detect CTCs because of their particular scarcity in complex peripheral blood. Herein, we describe an in situ-generated multivalent aptamer network-modified electrode interface for efficiently capturing and sensitively detecting CTCs in whole blood by electrochemistry. Such an interface was fabricated via rolling circle amplification extension of the electrode-immobilized primer/circular DNA complexes for the yield of long ssDNA strands with many repeated aptamer segments, which could achieve efficient capture of rare CTCs in a multivalent cooperative manner. The antibody and horseradish peroxidase-functionalized gold nanoparticles further specifically associated with the surface-bound CTCs and generated electrocatalytically amplified current outputs for highly sensitive detection of CTCs with an attractive detection limit of five cells. Also, the multivalent aptamer network interface could successfully distinguish the target cells from other control cells and achieve CTC detection in whole blood, demonstrating its promising potential for monitoring different rare CTCs in human blood.

Cooperation on Interdependent Networks by Means of Migration and Stochastic Imitation.

Evolutionary game theory in the realm of network science appeals to a lot of research communities, as it constitutes a popular theoretical framework for studying the evolution of cooperation in social dilemmas. Recent research has shown that cooperation is markedly more resistant in interdependent networks, where traditional network reciprocity can be further enhanced due to various forms of interdependence between different network layers. However, the role of mobility in interdependent networks is yet to gain its well-deserved attention. Here we consider an interdependent network model, where individuals in each layer follow different evolutionary games, and where each player is considered as a mobile agent that can move locally inside its own layer to improve its fitness. Probabilistically, we also consider an imitation possibility from a neighbor on the other layer. We show that, by considering migration and stochastic imitation, further fascinating gateways to cooperation on interdependent networks can be observed. Notably, cooperation can be promoted on both layers, even if cooperation without interdependence would be improbable on one of the layers due to adverse conditions. Our results provide a rationale for engineering better social systems at the interface of networks and human decision making under testing dilemmas.

Modeling of mixed convection in an enclosure using multiple regression, artificial neural network, and adaptive neuro-fuzzy interface system models

In this study, the heat transfer characteristics of laminar combined forced convection through a horizontal duct are obtained with the help of the numerical methods. The effect of the geometrical parameters of the cavity and Reynolds number on the heat transfer is investigated. New heat transfer correlation for hydrodynamically fully developed, laminar combined forced convection through a horizontal duct is proposed with an average error of 6.98% and R2 of 0.8625. The obtained correlation results are compared with the artificial neural network and adaptive neuro-fuzzy interface system models. Due to the obtained results, good agreement is identified between the numerical results and predicted adaptive neuro-fuzzy interface system results. In conclusion, it is seen that adaptive neuro-fuzzy interface system can predict the Nusselt number distribution with a higher accuracy than the developed correlation and the artificial neural network model. The developed adaptive neuro-fuzzy interface system model predicts the Nusselt number with 1.07% mean average percentage error and 0.9983 R2 value. The effect of the different training algorithms and their ability to predict Nusselt number distribution are examined. According to the results, the Bayesian regulation algorithm gives the best approach with a 2.235% error. According to the examination that is performed in this study, the adaptive neuro-fuzzy interface system is a powerful, robust tool that can be used with confidence for predicting the thermal performance.

Geometría del ancho de banda de un canal de comunicación

Este trabajo tiene por objeto mostrar los resultados de un estudio planteado con un grupo de 50 estudiantes de ingeniería en Telecomunicaciones a quienes se les aplicó la construcción cognitiva de los elementos geométricos en la determinación del ancho de banda de un canal como una prueba de aprendizaje, la instrucción Matemática en las dimensiones epistémica y cognitiva. Se implementó una estrategia didáctica y una metodología de construcción, diseñada sobre los elementos geométricos para razonar sobre probabilidad condicional. Las producciones se analizaron antes y después de la instrucción. El propósito era contribuir a la construcción del significado de la fórmula programada en el software o firmware de una interfaz de red, al favorecer la habilidad de efectuar la construcción cognitiva del canal de comunicación y su comportamiento en un escenario de trabajo. Los estudiantes que desarrollaron esta habilidad, mostraron menores dificultades en sus resoluciones y plantearon nuevas ideas sobre optimización del canal de comunicación.

Privacy-Preserving Non-Wearable Occupancy Monitoring System Exploiting Wi-Fi Imaging for Next-Generation Body Centric Communication.

Nano-scaled structures, wireless sensing, wearable devices, and wireless communications systems are anticipated to support the development of new next-generation technologies in the near future. Exponential rise in future Radio-Frequency (RF) sensing systems have demonstrated its applications in areas such as wearable consumer electronics, remote healthcare monitoring, wireless implants, and smart buildings. In this paper, we propose a novel, non-wearable, device-free, privacy-preserving Wi-Fi imaging-based occupancy detection system for future smart buildings. The proposed system is developed using off-the-shelf non-wearable devices such as Wi-Fi router, network interface card, and an omnidirectional antenna for future body centric communication. The core idea is to detect presence of person along its activities of daily living without deploying a device on person’s body. The Wi-Fi signals received using non-wearable devices are converted into time–frequency scalograms. The occupancy is detected by classifying the scalogram images using an auto-encoder neural network. In addition to occupancy detection, the deep neural network also identifies the activity performed by the occupant. Moreover, a novel encryption algorithm using Chirikov and Intertwining map-based is also proposed to encrypt the scalogram images. This feature enables secure storage of scalogram images in a database for future analysis. The classification accuracy of the proposed scheme is 91.1%.

Analysis of Visual Experience of Network Interaction Design Based on Cognitive Psychology

Web2.0 has led to the common age of the Internet. Users not only passively read information online, but also actively become information producers. Therefore, humanization has become an increasingly important topic in network interface design. Whether the design of the web interfaces is consistent with the cognitive characteristics of the user, and whether it is conducive to the organization and processing of the consciousness, will affect the effectiveness, efficiency and satisfaction of the user interface. This article explores the relationship between designers and users through literature and case analysis, starting from cognitive psychology. Through analysis of a series of psychological activities such as perception, the goal of humanizing the web interface is finally achieved. Cognitive psychology is an effective means to improve the level of web interface design in the Web2.0 era. Learning and research on it can promote the construction of user-friendly web sites that are easy to use and loved by users.

Trustworthy isolation of DMA devices

We present a mechanism to trustworthy isolate I/O devices with direct memory access (DMA), which ensures that an isolated I/O device cannot access sensitive memory regions. As a demonstrating platform, we use the network interface controller (NIC) of an embedded system. We develop a run-time monitor that forces NIC reconfigurations, defined by untrusted software, to satisfy a security rule. We formalized the NIC in the HOL4 interactive theorem prover and we verified the design of the isolation mechanism. The verification is based on an invariant that is proved to be preserved by all NIC operations and that ensures that all memory accesses address allowed memory regions only. We demonstrate our approach by extending an existing Virtual Machine Introspection (VMI) with the monitor. The resulting platform prevents code injection in a connected and untrusted Linux.