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Designing Heavy-Hitter detection algorithms for Programmable Switches

IEEE-ACM TRANSACTIONS ON NETWORKING 2020年第3期28卷 1172-1185页

作者： Ben Basat, Ran Chen, Xiaoqi Einziger, Gil Rottenstreich, Ori Harvard Univ Sch Engn & Appl Sci Cambridge MA 02138 USA Princeton Univ Dept Comp Sci Princeton NJ 08544 USA Ben Gurion Univ Negev Dept Comp Sci IL-84105 Beer Sheva Israel Technion IL-3200003 Haifa Israel

Programmable network switches promise flexibility and high throughput, enabling applications such as load balancing and traffic engineering. Network measurement is a fundamental building block for such applications, including tasks such as the identification of heavy hitters (largest flows) or the detection of traffic changes. However, high-throughput packet processing architectures place certain limitations on the programming model, such as restricted branching, limited capability for memory access, and a limited number of processing stages. These limitations restrict the types of measurement algorithms that can run on programmable switches. In this paper, we focus on the Reconfigurable Match Tables (RMT) programmable high-throughput switch architecture, and carefully examine its constraints on designing measurement algorithms. We demonstrate our findings while solving the heavy hitter problem. We introduce PRECISION, an algorithm that uses Partial Recirculation to find top flows on a programmable switch. By recirculating a small fraction of packets, PRECISION simplifies the access to stateful memory to conform with RMT limitations and achieves higher accuracy than previous heavy hitter detection algorithms that avoid recirculation. We also evaluate each of the adaptations made by PRECISION and analyze its effect on the measurement accuracy. Finally, we suggest two algorithms for the hierarchical heavy hitters detection problem in which the goal is identifying the subnets that send excessive traffic and are potentially malicious. To the best of our knowledge, our work is the first to do so on RMT switches.

关键词： Pipelines Throughput Memory management detection algorithms Task analysis Approximation algorithms Software defined networking measurement

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A METHODOLOGY FOR QUANTITATIVE PERFORMANCE EVALUATION OF detection algorithms

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1995年第12期4卷 1667-1674页

作者： KANUNGO, T JAISIMHA, MY PALMER, J HARALICK, RM UNIV WASHINGTON DEPT PSYCHOLSEATTLEWA 98195

We present a methodology for the quantitative performance evaluation of detection algorithms in computer vision. A common method is to generate a variety of input images by varying the image parameters and evaluate the performance of the algorithm, as algorithm parameters vary. Operating curves that relate the probability of misdetection and false alarm are generated for each parameter setting. Such an analysis does not integrate the performance of the numerous operating curves. In this paper, we outline a methodology for summarizing many operating curves into a few performance curves. This methodology is adapted from the human psychophysics literature and is general to any detection algorithm. The central concept is to measure the effect of variables in terms of the equivalent effect of a critical signal variable, which in turn facilitates the determination of the breakdown point of the algorithm. We demonstrate the methodology by comparing the performance of two-line detection algorithms.

关键词： Image edge detection Gratings Task analysis detection algorithms Detectors Performance evaluation Signal to noise ratio

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Quality Assessment Methods to Evaluate the Performance of Edge detection algorithms for Digital Image: A Systematic Literature Review

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IEEE ACCESS 2021年 9卷 87763-87776页

作者： Tariq, Nazish Hamzah, Rostam Affendi Ng, Theam Foo Wang, Shir Li Ibrahim, Haidi Univ Sains Malaysia Sch Elect & Elect Engn Engn Campus Nibong Tebal 14300 Malaysia Univ Tekn Malaysia Melaka Fak Teknol Kejuruteraan Elekt & Elekt Durian Tunggal 76100 Malaysia Univ Sains Malaysia Ctr Global Sustainabil Studies CGSS Hamzah Sendut Lib Level 5 Minden 11800 Malaysia Univ Pendidikan Sultan Idris Fac Art Comp & Creat Ind Tanjung Malim 35900 Malaysia

A segmentation process is usually required in order to analyze an image. One of the available segmentation approaches is by detecting the edges on the image. Up to now, there are many edge detection algorithms that researchers have proposed. Thus, the purpose of this systematic literature review is to investigate the available quality assessment methods that researchers have utilized to evaluate the performance of the edge detection algorithms. Due to the vast number of available literature in this area, we limit our search to only open-access publications. A systematic search in five publisher websites (i.e., IEEExplore, IET digital library, Wiley, MDPI, and Hindawi) and Scopus database was carried out to gather resources that are related to the edge detection algorithms. Seventy-three publications that are about developing or comparing edge detection algorithms have been chosen. From these publication samples, we have identified 17 quality assessment methods used by researchers. Among the popular quality assessment methods are visual inspection, processing time, confusion-matrix based measures, mean square error (MSE)-based measures, and figure of merit (FOM). This survey also indicates that although most of the researchers only use a small number of test images (i.e., less than 10 test images), there are available datasets with a larger number of images for digital image segmentation that researchers can utilize.

关键词： Image edge detection detection algorithms Quality assessment Systematics Bibliographies Image segmentation Digital images Digital image processing edge detection algorithm image segmentation assessment validation quality measures reviews

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A Survey on the detection algorithms for False Data Injection Attacks in Smart Grids

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IEEE TRANSACTIONS ON SMART GRID 2020年第3期11卷 2218-2234页

作者： Musleh, Ahmed S. Chen, Guo Dong, Zhao Yang Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia

Cyber-physical attacks are the main substantial threats facing the utilization and development of the various smart grid technologies. Among these attacks, false data injection attack represents a main category with its widely varied types and impacts that have been extensively reported recently. In addressing this threat, several detection algorithms have been developed in the last few years. These were either model-based or data-driven algorithms. This paper provides an intensive summary of these algorithms by categorizing them and elaborating on the pros and cons of each category. The paper starts by introducing the various cyber-physical attacks along with the main reported incidents in history. The significance and the impacts of the false data injection attacks are then reported. The concluding remarks present the main criteria that should be considered in developing future detection algorithms for the false data injection attacks.

关键词： Smart grids detection algorithms Explosions Security Pipelines Generators Malware Cyber-physical attacks data-driven detection algorithms false data injection machine learning model-based detection algorithms smart grid state estimation stealth attacks

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Fidelity Measurement on Signal detection algorithms with Application to AFM Imaging

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IEEE ACCESS 2018年 6卷 52831-52842页

作者： Ghosal, Sayan Salapaka, Murti Seagate Technol Shakopee MN 55379 USA Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA

Many signal processing and decision making algorithms reported in contemporary literature characterize the performance of the proposed methods utilizing decision error rates. However there is significant need for strategies that provide quantitative assessment of the fidelity of decisions made by the algorithms. This paper develops novel techniques utilizing which fidelity measures can be assigned quantitatively on some prevalent signal detection algorithms. The developed fidelity measurement methods with the detection algorithms are employed for topography imaging utilizing dynamic mode atomic force microscope (AFM). The AFM is a versatile metrology tool for interrogating material at the nano-scale. In spite of its remarkable achievements, a key issue that remains largely unaddressed is the assessment of fidelity of the measurement data. The developed paradigm facilitates user specific priority for either detection of sample features with high decision confidence or on not missing detection of true features. The fidelity measures presented here are suitable for real-time implementation. A detailed comparative study is presented to characterize the proposed signal detection algorithms and fidelity measurement techniques under practical AFM applications. Comprehensive simulation and experimental data corroborate the effectiveness of proposed methods.

关键词： Atomic force microscopy detection algorithms estimation Kalman filters observers scanning probe microscopy signal detection signal processing algorithms

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Pressure-detection algorithms A Suited Design

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IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE 2009年第5期28卷 35-40页

作者： Perfetto, J. C. Ruiz, A. G. Sirne, R. O. D'Attellis, C. E. Univ Buenos Aires Inst Ingn Biomed IIBM RA-1053 Buenos Aires DF Argentina Fernandez Hosp Syncope Lab Hyderabad Andhra Pradesh India Univ Nacl San Martin Buenos Aires DF Argentina Univ Favaloro Buenos Aires DF Argentina

Our approach is based on identifying specific characteristics of the arterial blood pressure (ABP) signal. During the development of the algorithm, we examined the signals and tried to extract the features that signals always share with other signals of the same type. These features permit acceptance of a portion of the signal as being part of arterial pressure or reject it as being an artifact. The algorithm first detects the occurrence of the systolic point and, thereafter, the diastolic point. The method we present here is designed to be used in adaptation mechanisms of the cardiovascular system assessment.

关键词： Signal processing Multiresolution analysis Epilepsy System testing detection algorithms Electrocardiography Electroencephalography Signal resolution Pathology Cardiovascular system

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Efficient detection algorithms for multi-input/multi-output systems by exploiting the non-circularity of transmitted signal source

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IET SIGNAL PROCESSING 2011年第2期5卷 180-186页

作者： Ding, Y. Wang, Y. Diouris, J. -F. Univ Nantes Ecole Polytech Lab IREENA F-44306 Nantes France

In this study, several new detection algorithms are proposed for multi-input/multi-output (MIMO) communication systems transmitting non-circular signals. Unlike the conventional receivers, the proposed detectors estimate the transmitted signal from both the received signal and its complex conjugate version. Analytical results quantifying the performance improvement are provided. As a typical example, extended zero-forcing (EZF) detector and extended minimum mean square error (EMMSE) detector are derived for the real signals. Computational complexity of the proposed algorithms remains the same order as that of the conventional zero-forcing (ZF). Simulation results show that both EZF and EMMSE detectors significantly outperform the conventional minimum mean square error (MMSE) detector, and that the ordered-successive-interference-cancelling (OSIC) version of the EZF (or EMMSE) detector has a quasi-optimal performance in terms of bit error rate (BER).

关键词： Electromagnetic compatibility and interference bit error rate error statistics ordered-successive-interference-cancelling extended zero-forcing detector quasioptimal performance multiinput/multioutput systems interference suppression transmitting noncircular signals complex conjugate version mean square error methods detection algorithms extended minimum mean square error Interpolation and function approximation (numerical analysis) computational complexity BER Radio links and equipment transmitted signal source MIMO communication Other topics in statistics

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A COMPARISON OF THE NOISE SENSITIVITY OF 9 QRS detection algorithms

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IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 1990年第1期37卷 85-98页

作者： FRIESEN, GM JANNETT, TC JADALLAH, MA YATES, SL QUINT, SR NAGLE, HT ALCATEL NETWORK SYST DEPT RES & DEV RES TRIANGLE PK NC USA BELL NO RES RES TRIANGLE PK NC USA N CAROLINA STATE UNIV DEPT ELECT & COMP ENGN RALEIGH NC 27695 USA UNIV N CAROLINA BIOMED ENGN CURRICULUM CHAPEL HILL NC 27514 USA UNIV ALABAMA DEPT ELECT ENGN BIRMINGHAM AL 35233 USA

The noise sensitivities of nine different QRS detection algorithms were measured for a normal, single-channel, lead-II, synthesized ECG corrupted with five different types of synthesized noise: electromyographic interference, 60-Hz power line interference, baseline drift due to respiration, abrupt baseline shift, and a composite noise constructed from all of the other noise types. The percentage of QRS complexes detected, the number of false positives, and the detection delay were measured. None of the algorithms were able to detect all QRS complexes without any false positives for all of the noise types at the highest noise level. algorithms based on amplitude and slope had the highest performance for EMG-corrupted ECG. An algorithm using a digital filter had the best performance for the composite-noise-corrupted data.< >

关键词： detection algorithms Electrocardiography Signal processing algorithms Noise level Noise measurement Performance analysis Application software Databases Gold Size measurement

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ADAPTIVE detection algorithms FOR MULTIPLE-TARGET SITUATIONS

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 1977年第4期13卷 338-343页

作者： RICKARD, JT DILLARD, GM ORINCON CORP LA JOLLACA 92037 NAVAL ELECTR LAB CTR SAN DIEGOCA 92152

The performance of a mean-level detector is considered for the case where one or more interfering target returns are present in the set of cells used in estimating the clutter-plus-noise level. A serious degradation of detection probability is demonstrated for all of the single-pulse Swerling target fluctuation models (i. e., cases 0, 2, and 4). Indeed, for fixed mean radar cross sections of the primary and interfering targets, the probability of detecting the primary target is asymptotic to values significantly less than unity as the signal-to-noise ratios of the returns approach infinity. A class of alternative adaptive detection procedures is proposed and analyzed. These procedures, based on ranking and censoring techniques, maintain acceptable performance in the presence of interfering targets, and require only a minor addition in hardware to a conventional mean-level detector.

关键词： detection algorithms Radar detection Fluctuations Detectors Clutter Degradation Radar cross section Hardware Doppler radar Laboratories

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JOINT CARRIER PHASE ESTIMATION AND DATA detection algorithms FOR MULTI-H CPM DATA-TRANSMISSION

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IEEE TRANSACTIONS ON COMMUNICATIONS 1986年第9期34卷 873-881页

作者： LIEBETREU, JM Department of Electrical Engineering University of Colorado Colorado Springs CO USA

A dynamic programming algorithm, developed in [1]-[4] for obtaining the joint estimate of carrier phase and data, is applied to multi h continuous phase modulation. A MAP estimator detects data and jointly tracks carrier phase consisting of a normal random walk phase jitter process. Monte Carlo computer simulations are used to evaluate the probability of error performance for two receivers employed in demodulation of multi- h CPM signals. A simplified algorithm is proposed which yields up to a tenfold reduction in computation time at the expense of less than 1 dB in signal-to-noise ratio at the error rates computed, and for suitable ranges of phase jitter increments variance.

关键词： Phase estimation detection algorithms Data communication Jitter Dynamic programming Heuristic algorithms Continuous phase modulation Phase detection Monte Carlo methods Computer simulation

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