1,720,968 research outputs found
A streaming approach to reveal crowded events from cellular data
No full textAnomaly detection has been a very popular research topics over the last few years and applies to many scenarios from different disciplines. This research focuses on crowded phenomena, and addresses the detection of popular events by looking for “anomalous” patterns in cellular traffic data. In particular, the paper elaborates upon previous proposals and presents two streaming algorithms based on the wavelet decomposition of traffic data. The new algorithms consume traffic samples as soon as they are available, elaborate the data in real time and possibly raise alarms upon threshold crossing. The effectiveness of the approach is assessed by using the public dataset containing the real cellular data acquired over the network of the most popular Italian traffic operator. The experiments prove that the streaming algorithms generally achieve performance comparable to that of their offline counterparts, and that the small degradation that may occasionally be observed is however well counterbalanced by the obvious advantage of detecting anomalies in real-time with no need to wait for the elaboration of overly long traffic timeseries
On the Impact of Memory Safety on Fast Network I/O
No full textRust is a multi-paradigm, general-purpose programming language that prioritizes performance, type safety, and fearless concurrency. At compile time, Rust is able to ensure memory and thread safety without relying on automated memory management techniques such as garbage collection. As a result, Rust is gaining significant popularity as a replacement for C/C++ in various domains where performance and reliability are paramount, such as systems programming, embedded devices, and networking.This paper attempts to critically evaluate the claims of high performance and memory safety associated with Rust, particularly in the context of low-level network programming. The approach involves rewriting Nethuns, a fast C-based network I/O library, using Rust. The Rust-based implementation of Nethuns is described in detail in this work, with a particular emphasis on explaining the design choices, highlighting the primary benefits gained in terms of safety and security, and addressing the challenges encountered throughout the process. The paper concludes with a performance evaluation of the library.The obtained results are promising: the Rust-based library ensures a significantly higher level of safety at compile time, with a modest performance trade-off
Accelerating network analytics with an on-NIC streaming engine
Full text linkData Stream Processing engines have recently emerged as powerful tools for simplifying the analysis of network telemetry data. Motivated by the ever-growing volume of data requiring analysis, cutting-edge approaches integrate them with programmable switches to filter out less relevant traffic and enhance their processing capabilities. In this paper, we propose an alternative solution: leveraging SmartNICs as high-performance accelerators for stream processing operations. SmartNICs are commonly deployed in datacenter networks, and their architecture is often characterized by numerous low-power processors that align seamlessly with the highly parallelizable computational requirements of standard streaming analysis frameworks. Starting from WindFlow, a state-of-the-art stream processor, we present an innovative architecture that enables the offloading of a portion of its computation to a commodity Netronome SmartNIC. We implemented the offload logic using eBPF, making our solution compatible with any NIC supporting this programming paradigm. We developed a diverse range of applications (i.e., flow metering, port scan detection and SYN flood attack detection) and show that our solution can analyze up to 40% more traffic compared to a pure software approach
Data Stream Processing in Software Defined Networks: Perspectives and Challenges
No full textThe new paradigm of network softwarization is pushing programmability and programming abstractions as key elements at different levels on both data and control planes of the network. However, the availability of programmable abstractions and devices per se is not sufficient to guarantee high-speed processing rates to network applications without the adoption of efficient programming models and accelerating methodologies. The paper discusses the possible sources of computation bottlenecks and proposes Data Stream Processing (DaSP) as a viable programming model for a unified scheme of accelerating data elaboration over both fast and slow data paths. Perspectives and implications of the adoption of DaSP are presented along with possible research directions
Mind the cost of telemetry data analysis
No full textData Stream Processing engines are emerging as a promising solution to efficiently process a continuous amount of telemetry information. In this poster, we compare four of them: Storm, Flink, Spark and WindFlow. The aim is to shed some lights on the best streaming engine for network traffic analysis
Atmospheric compensation of prisma data by means of a learning based approach
Full text linkAtmospheric compensation (AC) allows the retrieval of the reflectance from the measured at-sensor radiance and is a fundamental and critical task for the quantitative exploitation of hyperspectral data. Recently, a learning-based (LB) approach, named LBAC, has been proposed for the AC of airborne hyperspectral data in the visible and near-infrared (VNIR) spectral range. LBAC makes use of a parametric regression function whose parameters are learned by a strategy based on synthetic data that accounts for (1) a physics-based model for the radiative transfer, (2) the variability of the surface reflectance spectra, and (3) the effects of random noise and spectral miscalibration errors. In this work we extend LBAC with respect to two different aspects: (1) the platform for data acquisition and (2) the spectral range covered by the sensor. Particularly, we propose the extension of LBAC to spaceborne hyperspectral sensors operating in the VNIR and short-wave infrared (SWIR) portion of the electromagnetic spectrum. We specifically refer to the sensor of the PRISMA (PRecursore IperSpettrale della Missione Applicativa) mission, and the recent Earth Observation mission of the Italian Space Agency that offers a great opportunity to improve the knowledge on the scientific and commercial applications of spaceborne hyperspectral data. In addition, we introduce a curve fitting-based procedure for the estimation of column water vapor content of the atmosphere that directly exploits the reflectance data provided by LBAC. Results obtained on four different PRISMA hyperspectral images are presented and discussed
Data stream processing for packet-level analytics
Full text linkOne of the most challenging tasks for network operators is implementing accurate per-packet monitoring, looking for signs of performance degradation, security threats, and so on. Upon critical event detection, corrective actions must be taken to keep the network running smoothly. Implementing this mechanism requires the analysis of packet streams in a real-time (or close to) fashion. In a softwarized network context, Stream Processing Systems (SPSs) can be adopted for this purpose. Recent solutions based on traditional SPSs, such as Storm and Flink, can support the definition of general complex queries, but they show poor performance at scale. To handle input data rates in the order of gigabits per seconds, programmable switch platforms are typically used, although they offer limited expressiveness. With the proposed approach, we intend to offer high performance and expressive power in a unified framework by solely relying on SPSs for multicores. Captured packets are translated into a proper tuple format, and network monitoring queries are applied to tuple streams. Packet analysis tasks are expressed as streaming pipelines, running on general-purpose programmable network devices, and a second stage of elaboration can process aggregated statistics from different devices. Experiments carried out with an example monitoring application show that the system is able to handle realistic traffic at a 10 Gb/s speed. The same application scales almost up to 20 Gb/s speed thanks to the simple optimizations of the underlying framework. Hence, the approach proves to be viable and calls for the investigation of more extensive optimizations to support more complex elaborations and higher data rates
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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