2021 Advanced Communication Technologies and Signal Processing (ACTS)最新文献_第3页

B3R: A New Approach to BBR Congestion Control for Shallow Buffers 浅缓冲区BBR拥塞控制的一种新方法

2021 Advanced Communication Technologies and Signal Processing (ACTS) Pub Date : 2021-12-15 DOI: 10.1109/ACTS53447.2021.9708095

Tarun Singhania, W. Arif, D. Sen

{"title":"B3R: A New Approach to BBR Congestion Control for Shallow Buffers","authors":"Tarun Singhania, W. Arif, D. Sen","doi":"10.1109/ACTS53447.2021.9708095","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708095","url":null,"abstract":"The introduction of Bottleneck Bandwidth and Round-trip time (BBR), a state based Congestion Control Algorithm (CCA), has brought new insights into the way how modern network handles multitude of data across shared links for minimal delay and maximum bandwidth utilization. It claimed to be operating at Kleinrock’s optimal operating point without filling up buffers or having large packet losses. However, evaluation of BBR revealed that it displayed a high loss rate under certain operating conditions. The reason for high losses in BBR is the static increase of sending rate by a factor of 1.25 while probing for more bandwidth under small bottleneck buffer sizes, typically when buffer sizes are less than one times the product of Bandwidth and delay. High packet losses in short buffer sizes can lead to disruptive connections and poor application performance. To tackle this issue, we propose Bottleneck Bandwidth Buffer and Round-trip propagation time (B3R) which aims to actively estimate the bottleneck link buffer and then sets up a proper congestion control in short buffer scenarios to eliminate the high packet loss. The proposed model is evaluated on a testbed network, and the results showed that B3R reduced retransmissions by up to 80% as compared to BBR under short buffer scenarios.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133305568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Two-Stage CNN Based Channel Estimation for OFDM System 基于两阶段CNN的OFDM系统信道估计

2021 Advanced Communication Technologies and Signal Processing (ACTS) Pub Date : 2021-12-15 DOI: 10.1109/ACTS53447.2021.9708091

Annapurna Pradhan, Susmita Das, Deepak Dayalan

引用次数: 2

Multipath Modeling under Tank Environment for Underwater Acoustic Communication 水池环境下水声通信多径建模

2021 Advanced Communication Technologies and Signal Processing (ACTS) Pub Date : 2021-12-15 DOI: 10.1109/ACTS53447.2021.9708257

Sangram More, P. Bartakke, Monika Aggrawal

引用次数: 0

Design and Implementation of Automated Aquaponic System with Real-time Remote Monitoring 具有实时远程监控的水培系统的设计与实现

2021 Advanced Communication Technologies and Signal Processing (ACTS) Pub Date : 2021-12-15 DOI: 10.1109/ACTS53447.2021.9708396

Gnana Yashaswini Sriram, N. B. Sai Shibu

引用次数: 3

Spectral Efficiency Analysis of D2D-Enabled Massive MIMO Systems 支持d2d的大规模MIMO系统频谱效率分析

2021 Advanced Communication Technologies and Signal Processing (ACTS) Pub Date : 2021-12-15 DOI: 10.1109/ACTS53447.2021.9708386

Ajay Bhardwaj, D. Gurjar, Awanish Kumar

引用次数: 0

Contents of Conference Proceedings 会议记录内容

2021 Advanced Communication Technologies and Signal Processing (ACTS) Pub Date : 2021-12-15 DOI: 10.1109/drpt.2004.1337995

K. P. Wong, H. Rudnick

引用次数: 0

Statistical Description of Electrophysiological Features of Neurons across Layers of Human Cortex 人类皮层各层神经元电生理特征的统计描述

2021 Advanced Communication Technologies and Signal Processing (ACTS) Pub Date : 2021-12-15 DOI: 10.1109/ACTS53447.2021.9708234

S. Panda, Archita Hore, Ayan Chakraborty, S. Chakrabarti

{"title":"Statistical Description of Electrophysiological Features of Neurons across Layers of Human Cortex","authors":"S. Panda, Archita Hore, Ayan Chakraborty, S. Chakrabarti","doi":"10.1109/ACTS53447.2021.9708234","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708234","url":null,"abstract":"Modem deep learning technologies have helped scientists and engineers to solve many difficult problems in pattern recognition and decision making. Existing deep learning architectures face an important issue of high power dissipation. As an alternative solution spiking neural networks (SNN) are being recently developed by researchers with promise to overcome the bottleneck of power loss. An SNN is primarily inspired from a biological neuronal network consisting of real neurons. However, state of the art SNN models consist of layers with identical neurons which is not true in human cortex.In this study, a statistical approach is presented to show that the layers of a human cortex differ in terms of their member neurons. Neurons of different types are not identically distributed across the layers of a human cortex. Neurons are classified on the basis of key electrophysiological parameters such as spiking frequency, inter spike intervals, height and width of action potentials and energy dissipated per spike.The rich database provided by Allen Institute for Brain Science is used for the present study. It has been shown that spiking phenomenon is sparse across all the layers of a human cortex in temporal domain.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128471155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Secrecy Performance Analysis of RIS-Enabled Wireless Networks Over Rayleigh Fading Channels 瑞利衰落信道下ris -无线网络保密性能分析

2021 Advanced Communication Technologies and Signal Processing (ACTS) Pub Date : 2021-12-15 DOI: 10.1109/ACTS53447.2021.9708251

A. Yadav, S. Yadav, M. Shukla, D. Gurjar, Xingwang Li

引用次数: 3

Machine Learning-based Modulation Format Identification and Optical Performance Monitoring Techniques Implementation 基于机器学习的调制格式识别与光学性能监测技术实现

2021 Advanced Communication Technologies and Signal Processing (ACTS) Pub Date : 2021-12-15 DOI: 10.1109/ACTS53447.2021.9708283

Pukhrambam Puspa Devi, Vincent, J. W. Simatupang

{"title":"Machine Learning-based Modulation Format Identification and Optical Performance Monitoring Techniques Implementation","authors":"Pukhrambam Puspa Devi, Vincent, J. W. Simatupang","doi":"10.1109/ACTS53447.2021.9708283","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708283","url":null,"abstract":"In this paper, machine learning-based techniques are used to solve and analyze the modulation format recognition problem. The combination of intelligent software and high-performance hardware provides a large scope for innovation in optical networking. Machine learning algorithms can use a large amount of data available from the network monitors to learn and make the network more robust. This is a problem in optical communication that consists of defining the type of digital modulation process in which an electrical signal should be sent. A dataset to represent realistic transmission behaviors was generated using a simulator based on a Gaussian noise model. A multi-layer perceptron was used and tested with different architectures to show that a high level of accuracy is achievable with machine learning. An analysis of the input features was made by using the select K best features method. Finally, an attempt to visualize the data in 2-dimension was made using the Principal Component Analysis (PCA) and t-distributed Stochastic Neighbor Embedding (t-SNE) methods to reduce the dimensionality of the input features and see their relationships.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123594970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

The Impact of the Largest Lyapunov Exponent and Complexity of a Hyperchaotic System on the Secure Speech Communication 最大李雅普诺夫指数和超混沌系统复杂度对安全语音通信的影响

2021 Advanced Communication Technologies and Signal Processing (ACTS) Pub Date : 2021-12-15 DOI: 10.1109/ACTS53447.2021.9708232

Samuel Amde Gebereselassie, B. K. Roy

{"title":"The Impact of the Largest Lyapunov Exponent and Complexity of a Hyperchaotic System on the Secure Speech Communication","authors":"Samuel Amde Gebereselassie, B. K. Roy","doi":"10.1109/ACTS53447.2021.9708232","DOIUrl":"https://doi.org/10.1109/ACTS53447.2021.9708232","url":null,"abstract":"The magnitude of the largest Lyapunov exponent (LE) is used as a metric of chaoticity. The Kaplan-Yorke dimension is utilized to measure the complexity of a hyperchaotic system. A system having higher largest Lyapunov exponent has more chaoticity, and a higher Lyapunov dimension exhibits more complexity. We have performed a comparative analysis considering six different hyperchaotic systems to know the impact of Lyapunov exponents and complexity on the secure speech communication system. Each hyperchaotic system is used to generate the secure encrypted and decrypted speech signals by using the proposed two steps (masking and modulation) secure speech communication technique. The degree of security of the encrypted speech signal is analyzed by some available performance measures, such as encryption correlation coefficient, Segmental Spectral Signal to Noise Ratio (SSSNR), and peredogram. The performance measures resulted by using the considered six hyperchaotic systems (two systems with higher positive LE, two with medium and the rest two with low positive LE) are compared and observed that the largest positive Lyapunov exponent and Kaplan-Yorke dimension impact the performance of the secure speech communication. A higher value of the largest Lyapunov exponent and complexity of chaotic systems result in more security in the speech communication system.","PeriodicalId":201741,"journal":{"name":"2021 Advanced Communication Technologies and Signal Processing (ACTS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121283557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3