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2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST)最新文献

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On the Fairness of DCTCP and CUBIC in Cloud Data Center Networks 论云数据中心网络中DCTCP和CUBIC的公平性
Pub Date : 2021-07-05 DOI: 10.1109/MOCAST52088.2021.9493352
Konstantinos G. Tsiknas, Paraskevas I. Aidinidis, K. Zoiros
Data center networks (DCNs) hold a key role in information industry as the infrastructure for hosting cloud data services and related applications. The increasing number of customers using cloud services sets, however, new challenges for the efficient management of the DCN traffic handled by the transport protocols. TCP is adapted as the main transport control protocol in DCNs, but the standard congestion control algorithm it employs has been found to be very inefficient in providing a fair sharing of the available channel capacity among the competing DCN traffic flows. DCTCP and CUBIC are two promising TCP variants designed to resolve the fairness issues identified in these environments. In this paper, we evaluate the fairness properties of these two TCP variants in comparison to the conventional TCP Reno with the use of network simulator 3 (ns-3) in realistic DCN scenarios. Our results show that DTCP improves substantially the fairness properties of TCP, but it requires more buffer space for large number of flows; it also requires the intermediate switches to be Explicit Congestion Notification (ECN)-aware. CUBIC achieves very low queue occupancies, but it demonstrates low fairness when a large and a small set of flows compete at the output port of a bottleneck switch (TCP Outcast issue).
数据中心网络作为承载云数据服务和相关应用的基础设施,在信息产业中发挥着关键作用。然而,使用云服务的客户数量不断增加,对传输协议处理的DCN流量的有效管理提出了新的挑战。TCP被用作DCN中的主要传输控制协议,但它所采用的标准拥塞控制算法在提供竞争的DCN流量之间可用信道容量的公平共享方面效率非常低。DCTCP和CUBIC是两个很有前途的TCP变体,旨在解决这些环境中确定的公平性问题。在本文中,我们通过使用网络模拟器3 (ns-3)在现实的DCN场景中评估了这两种TCP变体与传统TCP Reno的公平性特性。我们的研究结果表明,DTCP大大提高了TCP的公平性,但它需要更多的缓冲空间来处理大量的流;它还要求中间交换机具有显式拥塞通知(ECN)意识。CUBIC实现了非常低的队列占用,但是当一大组流和一小组流在瓶颈交换机的输出端口竞争时(TCP Outcast问题),它表现出较低的公平性。
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引用次数: 1
Studying the impacts of loop unrolling and pipeline in the FPGA design of the Simon and RoadRunneR lightweght ciphers 研究了环展开和流水线对Simon和RoadRunneR轻量级密码FPGA设计的影响
Pub Date : 2021-07-05 DOI: 10.1109/MOCAST52088.2021.9493376
G. Georgiou, G. Theodoridis
In this work, the impacts of the loop unrolling and pipeline in the FPGA implementation of the Simon and RoadRunneR lightweight ciphers is studied. To achieve this, two basic architectures were used. In the first architecture only loop unrolling is applied while, the second one supports both the loop unrolling and pipeline. Using these architectures, three designs versions were developed, for each algorithm. The first and second ones concern individually the encryption and decryption procedures while, the third version is a hybrid one that supports both encryption and decryption. The metrics that were studied the area, frequency, throughput, throughput/area and energy consumption. The produced designs were implemented in Xilinx (Kintex-7) FPGA technology. Based on the implementation results, a detailed study on the above-mentioned design metrics was performed and important outcomes were derived.
在本工作中,研究了环展开和流水线对FPGA实现Simon和RoadRunneR轻量级密码的影响。为了实现这一点,使用了两个基本架构。在第一种体系结构中,只应用循环展开,而第二种体系结构同时支持循环展开和管道。使用这些架构,为每个算法开发了三个设计版本。第一个和第二个版本分别涉及加密和解密过程,而第三个版本是一个混合版本,同时支持加密和解密。研究的指标包括面积、频率、吞吐量、吞吐量/面积和能耗。生产的设计在Xilinx (Kintex-7) FPGA技术中实现。根据实施结果,对上述设计指标进行了详细的研究,并得出了重要的结果。
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引用次数: 0
Darknet Traffic Classification using Machine Learning Techniques 使用机器学习技术的暗网流量分类
Pub Date : 2021-07-05 DOI: 10.1109/MOCAST52088.2021.9493386
L. Iliadis, T. Kaifas
A Darknet is an overlay network within the Internet, and packets’ traffic originating from it is usually termed as suspicious. In this paper common machine learning classification algorithms are employed to identify Darknet traffic. A ROC analysis along with a feature importance analysis for the best classifier was performed, to provide a better visualisation of the results. The experiments were conducted in the new dataset CIC-Darknet2020 and the classifiers were trained to both binary and multiclass classification. In the first classification task, there were two classes: "Benign" and "Darknet", whereas in the second there were four classes: "Tor", "Non Tor", "VPN" and "Non VPN". An average prediction accuracy of over 98% was achieved with the implementation of Random Forest algorithm for both classification tasks. This is the first work, to the best of our knowledge providing a comprehensive performance evaluation of machine learning classifiers employed for Darknet traffic classification in the new dataset CIC-Darknet2020.
暗网是因特网上的一个覆盖网络,从暗网发出的信息包流量通常被认为是可疑的。本文采用常用的机器学习分类算法对暗网流量进行识别。进行ROC分析以及最佳分类器的特征重要性分析,以提供更好的结果可视化。在新的数据集CIC-Darknet2020上进行了实验,并对分类器进行了二分类和多分类的训练。在第一个分类任务中,有两个类别:“良性”和“暗网”,而在第二个分类任务中有四个类别:“Tor”,“非Tor”,“VPN”和“非VPN”。采用随机森林算法对两个分类任务的平均预测准确率均达到98%以上。据我们所知,这是第一项工作,为新数据集CIC-Darknet2020中用于暗网流量分类的机器学习分类器提供了全面的性能评估。
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引用次数: 21
ApproxQAM: High-Order QAM Demodulation Circuits with Approximate Arithmetic 近似算法的高阶QAM解调电路
Pub Date : 2021-07-05 DOI: 10.1109/MOCAST52088.2021.9493421
Vasileios Leon, I. Stratakos, Giorgos Armeniakos, G. Lentaris, D. Soudris
Modern mobile communication systems utilize increased bandwidth to provide advanced network performance and connectivity, all while their most computationally-intensive functions must be accelerated within the limited power envelope of embedded devices. In this paper, we improve the circuit complexity and throughput of a key digital function in the baseband processing chain, namely the high-order QAM demodulation. In particular, we explore 4 different demodulation algorithms, we employ both floating- and fixed-point arithmetic, and we insert approximations in the arithmetic units. In terms of accuracy of our most prominent implementations, i.e., for 64-QAM, our designs deliver BER values ranging from 10−1 to 10−4 for SNR 0−14dB. In terms of FPGA resources on Xilinx ZCU106, these 64-QAM designs achieve up to 98% reduction in LUT utilization compared to the accurate floating-point model of the same algorithm, and up to 122% increase in operating frequency. When targeting demodulation with high levels of accuracy, i.e., almost zero BER degradation with respect to that of the original floating-point model, the prevailing solution is the Approximate LLR algorithm configured with fixed-point arithmetic and 8-bit truncation, providing 81% decrease in LUTs and 13% increase in frequency to sustain a throughput of 323 Msamples/second.
现代移动通信系统利用增加的带宽来提供先进的网络性能和连接性,同时必须在嵌入式设备有限的功率范围内加速其最计算密集型功能。在本文中,我们改进了基带处理链中一个关键数字功能的电路复杂度和吞吐量,即高阶QAM解调。特别地,我们探索了4种不同的解调算法,我们采用浮点和定点算法,并在算术单元中插入近似值。就我们最突出的实现精度而言,即对于64-QAM,我们的设计提供的误码率范围为10−1至10−4,信噪比为0−14dB。在Xilinx ZCU106上的FPGA资源方面,与相同算法的精确浮点模型相比,这些64-QAM设计的LUT利用率降低了98%,工作频率提高了122%。当以高精度解调为目标时,即与原始浮点模型相比,几乎没有误码率下降,普遍的解决方案是配置定点算法和8位截断的Approximate LLR算法,提供81%的lut降低和13%的频率增加,以维持323 Msamples/second的吞吐量。
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引用次数: 2
Acoustic leak localization method based on signal segmentation and statistical analysis 基于信号分割和统计分析的声泄漏定位方法
Pub Date : 2021-07-05 DOI: 10.1109/MOCAST52088.2021.9493349
Georgios-Panagiotis Kousiopoulos, N. Karagiorgos, D. Kampelopoulos, V. Konstantakos, S. Nikolaidis
One of the most serious problems occurring in a pipeline network is the appearance of leaks. The process of detecting and localizing leaks in pipeline systems concerns a very extensive field of signal processing methods employed for this matter. In this paper a leak localization method combining the segmentation of acoustic leak signals, both in the time and in the frequency domain, with a statistical algorithm needed for dealing with the non-deterministic (stochastic) nature of these signals is proposed. This algorithm involves the use of cross-correlation techniques along with the grouping of the time-delay data in a histogram and selecting the bin with the largest number of elements as the one that provides the correct answer. The successful detection of the leak position requires the knowledge of the acoustic wave velocity in the pipe. In the present paper the calculation of the acoustic velocity is performed by the use of a PCB hammer to cover more realistic situations. The proposed leak localization method is tested experimentally in a laboratory setup containing a 67-meter steel pipeline and the results show that the presented method can localize leaks efficiently, since the average localization error is around 3%.
管道网络中出现的最严重的问题之一是泄漏的出现。检测和定位管道系统泄漏的过程涉及到用于此问题的信号处理方法的一个非常广泛的领域。本文提出了一种将声泄漏信号的时域和频域分割与处理这些信号的非确定性(随机)特性所需的统计算法相结合的泄漏定位方法。该算法涉及到使用相互关联技术以及在直方图中对延时数据进行分组,并选择具有最多元素的bin作为提供正确答案的bin。成功地检测泄漏位置需要知道管道中的声波速度。在本文中,为了涵盖更实际的情况,使用PCB锤来计算声速。在含67 m钢管管道的实验室环境中对所提出的泄漏定位方法进行了实验测试,结果表明,该方法能够有效地定位泄漏,平均定位误差在3%左右。
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引用次数: 0
A Simplified Model of Tantalum Oxide Based Memristor and Application in Memory Crossbars 氧化钽基忆阻器的简化模型及其在记忆栅中的应用
Pub Date : 2021-07-05 DOI: 10.1109/MOCAST52088.2021.9493384
V. Mladenov, S. Kirilov
In this article an enhanced and simplified alteration of a memristor model based on tantalum oxide is proposed. Its application in hybrid memory crossbars is presented. The suggested model is founded on the classical Hewlett Packard Ta2O5 memristor model including several main refinements – incorporation of a simple window function, enhancement of its efficiency applying rationalized expression for the current-voltage relation and by substitution of the Heaviside function with continuous and smooth logistic function. The memristor model’s parameters are obtained by collation to tentative current-voltage characteristics and applying procedure for parameters estimation. A LTSpice library model is generated in agreement to the considered memristor model. The modified model of tantalum oxide memristor is tested in a hybrid memory crossbar. After comparison to several basic models the major advantages of the suggested memristor model are demonstrated – better performance, higher speed of operation, improved adjustment process and a sound switching representation.
本文提出了一种基于氧化钽的忆阻器模型的改进和简化方法。介绍了其在混合存储横梁中的应用。该模型建立在经典的惠普Ta2O5记忆电阻器模型的基础上,包括几个主要的改进:引入一个简单的窗口函数,采用合理化的电流-电压关系表达式,用连续光滑的逻辑函数代替Heaviside函数,提高了窗口函数的效率。通过对暂定的电流-电压特性进行整理,并应用参数估计程序,得到了忆阻器模型的参数。生成与所考虑的忆阻器模型一致的LTSpice库模型。改进的氧化钽忆阻器模型在混合记忆棒上进行了测试。通过与几种基本模型的比较,证明了所提出的忆阻器模型的主要优点:性能更好,运行速度更快,调整过程改进,开关表示良好。
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引用次数: 4
iPONICS: IoT Monitoring and Control for Hydroponics iPONICS:水培物联网监测与控制
Pub Date : 2021-07-05 DOI: 10.1109/MOCAST52088.2021.9493387
K. Tatas, Ahmad Al-Zoubi, A. Antoniou, D. Zolotareva
This paper presents the design, and implementation of an intelligent, low-cost IoT-based control and monitoring system for hydroponics greenhouses. The system is based on three types of sensor nodes: The main (master) node is responsible for controlling the pump, monitoring the quality of the water in the greenhouse and aggregating and transmitting the data from the slave nodes. Environment sensing slave nodes that monitor the ambient conditions in the greenhouse and transmit the data to the main node. Security nodes that monitor activity (movement in the area). The system monitors water quality and greenhouse temperature and humidity, ensuring that crops grow under the optimal conditions according to hydroponics guidelines. Remote monitoring for the greenhouse keepers is facilitated by monitoring these parameters by connecting to a website. The system is optimized for low power consumption in order to facilitate off-grid operation.
本文介绍了一种基于物联网的水培温室智能低成本控制与监控系统的设计与实现。该系统基于三种类型的传感器节点:主(主)节点负责控制水泵,监测温室内的水质,汇总和传输从节点的数据。环境感知从节点,监测温室内的环境条件并将数据传输到主节点。监视活动(区域内的移动)的安全节点。该系统监测水质和温室温度和湿度,确保作物在最佳条件下根据水培指导方针生长。通过连接到网站监测这些参数,便于温室管理员进行远程监控。该系统针对低功耗进行了优化,以便于离网运行。
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引用次数: 9
Using Genetic Algorithms to Optimize the Instruction-Set Encoding on Processor Cores 利用遗传算法优化处理器核心上的指令集编码
Pub Date : 2021-07-05 DOI: 10.1109/MOCAST52088.2021.9493406
M. Weißbrich, Javier Andrés Moreno-Medina, G. P. Vayá
An optimized instruction-set encoding can reduce the silicon area and power consumption of a processor architecture implementation. However, the design space of the input encoding problem is of factorial growth with the number of instruction patterns, so effective heuristics and an automated exploration tool are required to facilitate instruction-set encoding optimization in a processor design flow. This paper proposes a novel approach based on genetic algorithms to automatically optimize the instruction-set encoding of a specific processor architecture, reducing the silicon area and power consumption requirements for specific applications and hardware implementation technologies. Furthermore, an open-source tool, called VANAGA, is presented, which implements the proposed approach and allows flexible adaptation to custom instruction-set optimization scenarios. The tool flow is evaluated with an exemplary 65 nm standard cell ASIC implementation of a minimal controller architecture with 4-bit wide opcodes (NanoController). For different optimization scenarios, logic silicon area and total power consumption vary within a design space range of 6.3% and 0.46% for different instruction-set encodings, respectively.
优化的指令集编码可以减少处理器架构实现的硅面积和功耗。然而,输入编码问题的设计空间随着指令模式的数量呈阶乘增长,因此需要有效的启发式和自动探索工具来促进处理器设计流程中的指令集编码优化。本文提出了一种基于遗传算法的新方法来自动优化特定处理器架构的指令集编码,从而减少特定应用和硬件实现技术的硅面积和功耗要求。此外,提出了一个名为VANAGA的开源工具,它实现了所提出的方法,并允许灵活地适应自定义指令集优化场景。工具流通过一个典型的65纳米标准单元ASIC实现,该ASIC实现了具有4位宽操作码的最小控制器架构(NanoController)。在不同优化方案下,不同指令集编码的逻辑硅面积和总功耗分别在6.3%和0.46%的设计空间范围内变化。
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引用次数: 2
Comparing Machine Learning Methods for Air-to-Ground Path Loss Prediction 空对地路径损失预测的机器学习方法比较
Pub Date : 2021-07-05 DOI: 10.1109/MOCAST52088.2021.9493374
G. Vergos, S. Sotiroudis, G. Athanasiadou, G. Tsoulos, S. Goudos
Machine Learning-based models gain increasingly momentum regarding the problem of path loss prediction. The work at hand deploys four machine learning algorithms (k Nearest Neighbors - kNN, Support Vector Regression - SVR, Random Forest - RF and AdaBoost), in order to simulate the radio coverage provided from a flying base station in the greek city of Tripolis. Their comparison shows that tree-based ensemble models (RF and AdaBoost) can be used as fast and reliable alternatives to the Ray Tracing technique.
基于机器学习的模型在路径损失预测问题上获得了越来越大的发展势头。手头的工作部署了四种机器学习算法(k最近邻- kNN,支持向量回归- SVR,随机森林- RF和AdaBoost),以模拟希腊城市Tripolis飞行基站提供的无线电覆盖。他们的比较表明,基于树的集成模型(RF和AdaBoost)可以作为射线追踪技术的快速可靠的替代方案。
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引用次数: 1
On the Realization of Power-Law Based Impedance Functions: Application to Edible Drinks 基于幂律的阻抗函数的实现:在食用饮料中的应用
Pub Date : 2021-07-05 DOI: 10.1109/MOCAST52088.2021.9493343
S. Kapoulea, C. Psychalinos, A. Elwakil
A novel procedure for compact realization of complex, multiple-parameter impedance functions is introduced in this paper. The concept is based on the consideration of the whole impedance function and the approximation of its frequency characteristics through a suitable curve-fitting-based algorithm, instead of separately approximating the intermediate terms of the function. In this way, the total impedance is implemented by a topology which is based on one transfer function, offering the benefit of reduced complexity. The impedance function that describes the electrical properties of edible drinks can be considered as a characteristic example and, therefore, is used for the verification of the proposed concept. Different samples of drinks, red wine from Bairrada, semi-skimmed and organic semi- skimmed milk, are considered with the behavior of the proposed schemes being evaluated through simulation and experimental results.
本文介绍了一种简化实现复杂多参数阻抗函数的新方法。该概念基于对整个阻抗函数的考虑,并通过合适的基于曲线拟合的算法逼近其频率特性,而不是单独逼近函数的中间项。通过这种方式,总阻抗由基于一个传递函数的拓扑实现,从而降低了复杂性。描述可食用饮料电性能的阻抗函数可以被视为一个典型的例子,因此,用于验证所提出的概念。以Bairrada红葡萄酒、半脱脂牛奶和有机半脱脂牛奶等不同的饮料样品为研究对象,通过模拟和实验结果对所提方案的性能进行了评价。
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引用次数: 0
期刊
2021 10th International Conference on Modern Circuits and Systems Technologies (MOCAST)
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