Academic literature on the topic 'Applicative level packets processing'
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Journal articles on the topic "Applicative level packets processing"
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Fais, Alessandra, Giuseppe Lettieri, Gregorio Procissi, Stefano Giordano, and Francesco Oppedisano. "Data Stream Processing for Packet-Level Analytics." Sensors 21, no. 5 (March 3, 2021): 1735. http://dx.doi.org/10.3390/s21051735.
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One 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.
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Ermakov, R. N. "CLASSIFICATION OF NETWORK PROTOCOLS WITH APPLICATION OF MACHINE LEARNING METHODS AND FUZZY LOGIC ALGORITHMS IN TRAFFIC ANALYSIS SYSTEMS." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 189 (March 2020): 37–48. http://dx.doi.org/10.14489/vkit.2020.03.pp.037-048.
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This paper presents a new effective approach to analyzing network traffic in order to determine the protocol of information exchange. A brief description of the structure of the algorithm for classifying network packets by belonging to one of the known network protocols is given. To define the protocol, the principle of high-speed one-packet classification is used, which consists in analyzing the information transmitted in each particular packet. Elements of behavioral analysis are used, namely, the transition states of information exchange protocols are classified, which allows to achieve a higher level of accuracy of classification and a higher degree of generalization in new test samples. The topic of the article is relevant in connection with the rapid growth of transmitted traffic, including malicious traffic, and the emergence of new technologies for transmitting and processing information. The article analyzes the place of traffic analysis systems among other information security systems, describes the tasks that they allow to solve. It is shown that when recognizing the internal state in which a particular protocol may be in the process of information exchange at the handshake stage, a classifier of network packets of the application level can be useful. To classify network packets, we used fuzzy logic algorithms (Mamdani model) and machine learning methods (neural network solutions based on logistic regression). The paper presents 4 stages of developing a network packet classifier – monitoring and collecting packet statistics of the most famous network traffic protocols, preprocessing primary packet statistics, building a classifier for network packets and testing. The test results of the constructed software module capable of identifying network protocols for information exchange are demonstrated.
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Kamble, Suchita, and N. N. Mhala. "Controller for Network Interface Card on FPGA." International Journal of Reconfigurable and Embedded Systems (IJRES) 1, no. 2 (July 1, 2012): 55. http://dx.doi.org/10.11591/ijres.v1.i2.pp55-58.
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The continuing advances in the performance of network servers make it essential for network interface cards (NICs) to provide more sophisticated services and data processing. Modern network interfaces provide fixed functionality and are optimized for sending and receiving large packets. Network interface cards allow the operating system to send and receive packets through the main memory to the network. The operating system stores and retrieves data from the main memory and communicates with the NIC over the local interconnect, usually a peripheral component interconnect bus (PCI). Most NICs have a PCI hardware interface to the host server, use a device driver to communicate with the operating system and use local receive and transmit storage buffers. NICs typically have a direct memory access (DMA) engine to transfer data between host memory and the network interface memory. In addition, NICs include a medium access control (MAC) unit to implement the link level protocol for the underlying network such as Ethernet, and use a signal processing hardware to implement the physical (PHY) layer defined in the network. To execute and synchronize the above operations NICs also contents controller whose architecture is customized for network data transfer. In this paper we present the architecture of application specific controller that can be used in NICs.
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Kim, Beom-Su, Sangdae Kim, Kyong Hoon Kim, Tae-Eung Sung, Babar Shah, and Ki-Il Kim. "Adaptive Real-Time Routing Protocol for (m,k)-Firm in Industrial Wireless Multimedia Sensor Networks." Sensors 20, no. 6 (March 14, 2020): 1633. http://dx.doi.org/10.3390/s20061633.
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Many applications are able to obtain enriched information by employing a wireless multimedia sensor network (WMSN) in industrial environments, which consists of nodes that are capable of processing multimedia data. However, as many aspects of WMSNs still need to be refined, this remains a potential research area. An efficient application needs the ability to capture and store the latest information about an object or event, which requires real-time multimedia data to be delivered to the sink timely. Motivated to achieve this goal, we developed a new adaptive QoS routing protocol based on the (m,k)-firm model. The proposed model processes captured information by employing a multimedia stream in the (m,k)-firm format. In addition, the model includes a new adaptive real-time protocol and traffic handling scheme to transmit event information by selecting the next hop according to the flow status as well as the requirement of the (m,k)-firm model. Different from the previous approach, two level adjustment in routing protocol and traffic management are able to increase the number of successful packets within the deadline as well as path setup schemes along the previous route is able to reduce the packet loss until a new path is established. Our simulation results demonstrate that the proposed schemes are able to improve the stream dynamic success ratio and network lifetime compared to previous work by meeting the requirement of the (m,k)-firm model regardless of the amount of traffic.
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MUROOKA, TAKAHIRO, AKIRA NAGOYA, TOSHIAKI MIYAZAKI, HIROYUKI OCHI, and YUKIHIRO NAKAMURA. "NETWORK PROCESSOR FOR HIGH-SPEED NETWORK AND QUICK PROGRAMMING." Journal of Circuits, Systems and Computers 16, no. 01 (February 2007): 65–79. http://dx.doi.org/10.1142/s0218126607003502.
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The paper describes the concept, architecture, and prototype test results of a packet processor that enables us to implement an application-specific high-speed packet processing system without expert-level programming skills. This processor has a pipelined processing architecture and features coarse-grained instructions that are based on the data formats of the telecommunication packet. Using this processor, target applications can be implemented within a short working period without degrading the processing performance. We implemented a prototype system to evaluate its packet propagation delay and packet forwarding performance. The measured results suggest that the architecture is useful for packet processing on high-speed telecommunication networks.
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omran alkaam, nora. "Image Compression by Wavelet Packets." Oriental journal of computer science and technology 11, no. 1 (March 20, 2018): 24–28. http://dx.doi.org/10.13005/ojcst11.01.05.
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This research implements Image processing to reduce the size of image without losing the important information This paper aims to determine the best wavelet to compress the still image at a particular decomposition level using wavelet packet transforms.
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Ahmadi, Mahmood, and Stephan Wong. "A Cache Architecture for Counting Bloom Filters: Theory and Application." Journal of Electrical and Computer Engineering 2011 (2011): 1–10. http://dx.doi.org/10.1155/2011/475865.
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Within packet processing systems, lengthy memory accesses greatly reduce performance. To overcome this limitation, network processors utilize many different techniques, for example, utilizing multilevel memory hierarchies, special hardware architectures, and hardware threading. In this paper, we introduce a multilevel memory architecture for counting Bloom filters. Based on the probabilities of incrementing of the counters in the counting Bloom filter, a multi-level cache architecture called the cached counting Bloom filter (CCBF) is presented, where each cache level stores the items with the same counters. To test the CCBF architecture, we implement a software packet classifier that utilizes basic tuple space search using a 3-level CCBF. The results of mathematical analysis and implementation of the CCBF for packet classification show that the proposed cache architecture decreases the number of memory accesses when compared to a standard Bloom filter. Based on the mathematical analysis of CCBF, the number of accesses is decreased by at least 53%. The implementation results of the software packet classifier are at most 7.8% (3.5% in average) less than corresponding mathematical analysis results. This difference is due to some parameters in the packet classification application such as number of tuples, distribution of rules through the tuples, and utilized hashing functions.
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Korobeynikov, A. V. "Synthesis of a packet of pulse with phase manipulation with side lobes level 1/N at incoherent accumulation." Issues of radio electronics 49, no. 5 (July 5, 2020): 28–34. http://dx.doi.org/10.21778/2218-5453-2020-5-28-34.
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The paper is devoted to the problem of choosing a probing radar signal using optimal processing of a packet of pulses with unknown initial phases. A method for synthesizing a packet of phase-coded pulses is proposed, the total autocorrelation function (ACF) of which, with coordinated filtering and incoherent accumulation, has a side lobes level (SLL) of 1/N. The search criteria for binary codes for phase manipulation of a signal that are potentially capable of forming packets of pulses with relative SLL of 1/N are formulated and justified. An algorithm has been developed for searching codes with a given ACF using the exhaustive search method. A method is proposed for forming the composition of a packets of pulses based on the exhaustive search method. A number of values of the code N duration were determined for which there are packets of pulses with a relative SLL of the total ACF equal to 1/N with coordinated filtering and incoherent accumulation.
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ČASTOVÁ, NINA, DAVID HORÁK, and ZDENĚK KALÁB. "DESCRIPTION OF SEISMIC EVENTS USING WAVELET TRANSFORM." International Journal of Wavelets, Multiresolution and Information Processing 04, no. 03 (September 2006): 405–14. http://dx.doi.org/10.1142/s0219691306001336.
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This paper deals with engineering application of wavelet transform for processing of real seismological signals. Methodology for processing of these slight signals using wavelet transform is presented in this paper. Briefly, three basic aims are connected with this procedure:. 1. Selection of optimal wavelet and optimal wavelet basis B opt for selected data set based on minimal entropy: B opt = arg min B E(X,B). The best results were reached by symmetric complex wavelets with scaling coefficients SCD-6. 2. Wavelet packet decomposition and filtration of data using universal criterion of thresholding of the form [Formula: see text], where σ is minimal variance of the sum of packet decomposition of chosen level. 3. Cluster analysis of decomposed data. All programs were elaborated using program MATLAB 5.
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Neeb, C., M. J. Thul, and N. Wehn. "Application driven evaluation of network on chip architectures forcation parallel signal processing." Advances in Radio Science 2 (May 27, 2005): 181–86. http://dx.doi.org/10.5194/ars-2-181-2004.
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Abstract. Today’s signal processing applications exhibit steadily increasing throughput requirements which can be achieved by parallel architectures. However, efficient communication is mandatory to fully exploit their parallelism. Turbo-Codes as an instance of highly efficient forward-error correction codes are a very good application to demonstrate the communication complexity in parallel architectures. We present a network-on-chip approach to derive an optimal communication architecture for a parallel Turbo-Decoder system. The performance of such a system significantly depends on the efficiency of the underlying interleaver network to distribute data among the parallel units. We focus on the strictly orthogonal n-dimensional mesh, torus and k-ary-n cube networks comparing deterministic dimension-order and partially adaptive negative- first and planar-adaptive routing algorithms. For each network topology and routing algorithm, input- and output-queued packet switching schemes are compared on the architectural level. The evaluation of candidate network architectures is based on performance measures and implementation cost to allow a fair trade-off.
Dissertations / Theses on the topic "Applicative level packets processing"
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Trabé, Patrick. "Infrastructure réseau coopérative et flexible de défense contre les attaques de déni de service distribué." Toulouse 3, 2006. http://www.theses.fr/2006TOU30288.
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Les attaques par déni de service distribué (DDoS, Distributed Denial of Service) consistent à limiter ou à empêcher l'accès à un service informatique. La disponibilité du service proposé par la victime est altérée soit par la consommation de la bande passante disponible sur son lien, soit à l'aide d'un nombre très important de requêtes dont le traitement surconsomme les ressources dont elle dispose. Le filtrage des DDoS constitue aujourd'hui encore un problème majeur pour les opérateurs. Le trafic illégitime ne comporte en effet que peu ou pas de différences par rapport au trafic légitime. Ces attaques peuvent ensuite tirer parti et attaquer des services disposés dans le réseau. L'approche présentée dans cette thèse se veut pragmatique et cherche à aborder ce problème suivant deux angles ; à savoir contenir l'aspect dynamique et distribué de ces attaques d'une part, et être capable de préserver le trafic légitime et le réseau d'autre part. Nous proposons dans ce but une architecture distribuée de défense comportant des nœuds de traitement associés aux routeurs des points de présence et d'interconnexion du réseau de l'opérateur. Ces nœuds introduisent dans le réseau, par le biais d'interfaces ouvertes, la programmabilité qui apporte la flexibilité et la dynamicité requises pour la résolution du problème. Des traitements de niveau réseau à applicatif sur les datagrammes sont ainsi possibles, et les filtrages sont alors exempts de dommages collatéraux. Un prototype de cette architecture permet de vérifier les concepts que nous présentonsThe goal of Distributed Denial of Service attacks (DDoS) is to prevent legitimate users from using a service. The availability of the service is attacked by sending altered packets to the victim. These packets either consume a large part of networks bandwidth, or create an artificial consumption of victim’s key resources such as memory or CPU. DDoS’ filtering is still an important problem for network operators since illegitimate traffics look like legitimate traffics. The discrimination of both classes of traffics is a hard task. Moreover DDoS victims are not limited to end users (e. G. Web server). The network is likely to be attacked itself. The approach presented in this thesis is pragmatic. Firstly it seeks to control dynamic and distributed aspects of DDoS. Secondly it looks for protecting legitimate traffics and the network against collateral damages. Thus we propose a distributed infrastructure of defense based on nodes dedicated to the analysis and the filtering of the illegitimate traffic. Each node is associated with one POP router or interconnection router in order to facilitate its integration into the network. These nodes introduce the required programmability through open interfaces. The programmability offers applicative level packets processing, and thus treatments without collateral damages. A prototype has been developed. It validates our concepts
Book chapters on the topic "Applicative level packets processing"
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Kim, Jeong Seob, Dae Sung Lee, Ki Chang Kim, and Jae Hyun Park. "Ensuring Immediate Processing of Real-Time Packets at Kernel Level." In Frontiers of High Performance Computing and Networking – ISPA 2006 Workshops, 738–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11942634_76.
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Toroczkai, Zoltan, and György Korniss. "Scalability, Random Surfaces, and Synchronized Computing Networks." In Computational Complexity and Statistical Physics. Oxford University Press, 2005. http://dx.doi.org/10.1093/oso/9780195177374.003.0020.
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In most cases, it is impossible to describe and understand complex system dynamics via analytical methods. The density of problems that are rigorously solvable with analytic tools is vanishingly small in the set of all problems, and often the only way one can reliably obtain a system-level understanding of such problems is through direct simulation. This chapter broadens the discussion on the relationship between complexity and statistical physics by exploring how the computational scalability of parallelized simulation can be analyzed using a physical model of surface growth. Specifically, the systems considered here are made up of a large number of interacting individual elements with a finite number of attributes, or local state variables, each assuming a countable number (typically finite) of values. The dynamics of the local state variables are discrete events occurring in continuous time. Between two consecutive updates, the local variables stay unchanged. Another important assumption we make is that the interactions in the underlying system to be simulated have finite range. Examples of such systems include: magnetic systems (spin states and spin flip dynamics); surface growth via molecular beam epitaxy (height of the surface, molecular deposition, and diffusion dynamics); epidemiology (health of an individual, the dynamics of infection and recovery); financial markets (wealth state, buy/sell dynamics); and wireless communications or queueing systems (number of jobs, job arrival dynamics). Often—as in the case we study here—the dynamics of such systems are inherently stochastic and asynchronous. The simulation of such systems is nontrivial, and in most cases the complexity of the problem requires simulations on distributed architectures, defining the field of parallel discrete-event simulations (PDES) [186, 367, 416]. Conceptually, the computational task is divided among n processing elements (PEs), where each processor evolves the dynamics of the allocated piece. Due to the interactions among the individual elements of the simulated system (spins, atoms, packets, calls, etc.) the PEs must coordinate with a subset of other PEs during the simulation. For example, the state of a spin can only be updated if the state of the neighbors is known. However, some neighbors might belong to the computational domain of another PE, thus, message passing will be required in order to preserve causality.
Conference papers on the topic "Applicative level packets processing"
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Odegbile, Olufemi, Chaoyi Ma, Shigang Chen, Dimitrios Melissourgos, and Haibo Wang. "Hierarchical Virtual Bitmaps for Spread Estimation in Traffic Measurement." In 11th International Conference on Computer Science and Information Technology (CCSIT 2021). AIRCC Publishing Corporation, 2021. http://dx.doi.org/10.5121/csit.2021.110718.
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This paper introduces a hierarchical traffic model for spread measurement of network traffic flows. The hierarchical model, which aggregates lower level flows into higher-level flows in a hierarchical structure, will allow us to measure network traffic at different granularities at once to support diverse traffic analysis from a grand view to fine-grained details. The spread of a flow is the number of distinct elements (under measurement) in the flow, where the flow label (that identifies packets belonging to the flow) and the elements (which are defined based on application need) can be found in packet headers or payload. Traditional flow spread estimators are designed without hierarchical traffic modeling in mind, and incur high overhead when they are applied to each level of the traffic hierarchy. In this paper, we propose a new Hierarchical Virtual bitmap Estimator (HVE) that performs simultaneous multi-level traffic measurement, at the same cost of a traditional estimator, without degrading measurement accuracy. We implement the proposed solution and perform experiments based on real traffic traces. The experimental results demonstrate that HVE improves measurement throughput by 43% to 155%, thanks to the reduction of perpacket processing overhead. For small to medium flows, its measurement accuracy is largely similar to traditional estimators that work at one level at a time. For large aggregate and base flows, its accuracy is better, with up to 97% smaller error in our experiments.
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Huang, Liling, Ahmad Beirami, Mohsen Sardari, Faramarz Fekri, Bo Liu, and Lin Gui. "Packet-level clustering for memory-assisted compression of network packets." In 2014 Sixth International Conference on Wireless Communications and Signal Processing (WCSP). IEEE, 2014. http://dx.doi.org/10.1109/wcsp.2014.6992186.
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R. Simpson, William, and Kevin E. Foltz. "Network Defense in an End-to-End Paradigm." In 9th International Conference on Natural Language Processing (NLP 2020). AIRCC Publishing Corporation, 2020. http://dx.doi.org/10.5121/csit.2020.101414.
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Network defense implies a comprehensive set of software tools to preclude malicious entities from conducting nefarious activities. For most enterprises at this time, that defense builds upon a clear concept of the fortress approach. Many of the requirements are based on inspection and reporting prior to delivery of the communication to the intended target. These inspections require decryption of packets when encrypted. This decryption implies that the defensive suite has access to the private keys of the servers that are the target of communication. This is in contrast to an end-to-end paradigm where known good entities can communicate directly with each other. In an end-to-end paradigm, maintaining confidentiality through unbroken end-toend encryption, the private key resides only with the holder-of-key in the communication and on a distributed computation of inspection and reporting. This paper examines a formulation that is pertinent to the Enterprise Level Security (ELS) framework.