Article
Computer Science, Information Systems
Arman Pashamokhtari, Norihiro Okui, Masataka Nakahara, Ayumu Kubota, Gustavo Batista, Hassan Habibi Gharakheili
Summary: This article examines the challenges of developing and applying data-driven inference models when labeled data is limited and the distribution of data changes over time and space. The study shows that dynamically selecting the best model and using unlabeled data for inference can achieve high accuracy.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Chemistry, Multidisciplinary
Xianlong Dai, Guang Cheng, Ziyang Yu, Ruixing Zhu, Yali Yuan
Summary: The results of this paper are applicable in the fields related to network measurement, especially in network traffic sampling, network traffic measurement, and finding top-k elephant flows. With encrypted traffic accounting for 95% of the total traffic in the backbone network, one of the key challenges is finding the top-k elephant flows. This paper proposes a novel algorithm called MSLCFinder, which achieves over 97% precision with extremely limited hardware resources through counting and uth-level multi-sampling in a limited resource environment.
APPLIED SCIENCES-BASEL
(2023)
Review
Computer Science, Information Systems
Jacek Krupski, Waldemar Graniszewski, Marcin Iwanowski
Summary: This paper surveys various CNN-based traffic analysis methods, with a focus on the importance of data transformation schemes in this field. Due to the different structures of network traffic data and machine learning data, it is crucial to study how to transform the data.
Article
Automation & Control Systems
Teresa Pamula, Renata Zochowska
Summary: In this article, a new method for predicting OD matrix based on traffic data using deep learning is proposed. The method eliminates the need for complex data acquisition and processing, and achieves high accuracy and resistance to missing data. A case study conducted in a medium-sized city in Poland demonstrates the practical implementation potential in real-time traffic assignment systems. The method does not require questionnaire research or detailed spatial development information.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Telecommunications
Amin Jamali, Mehdi Berenjkoub, Hossein Saidi, Behrouz Shahgholi Ghahfarokhi
Summary: In this paper, a model for quantifying the survivability of networks carrying complex traffic flows is proposed. The model takes into account the general multi-rate and heterogeneous nature of complex network traffic, where individual bandwidth demands can aggregate in complex, nonlinear ways. The study investigates arbitrary and known topologies, as well as independent and dependent failure scenarios and deterministic and random traffic models. Finally, survivability evaluation results for different network configurations are provided, showing that using about 50% of the link capacity in networks with a relatively high number of links can keep the blocking probability near zero even in the case of a limited number of failures.
DIGITAL COMMUNICATIONS AND NETWORKS
(2023)
Article
Computer Science, Information Systems
Ramin Mohammadi, Sedat Akleylek, Ali Ghaffari, Alireza Shirmarz
Summary: This paper discusses the problem of network resource configuration using Software Defined Network (SDN). By building a model that classifies applications based on the type of network flow and optimizes resource allocation, the proposed model improves Quality of Service (QoS) while maximizing network utilization.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Geosciences, Multidisciplinary
Martin Strohmeier, Xavier Olive, Jannis Lubbe, Matthias Schaefer, Vincent Lenders
Summary: The OpenSky Network is a non-profit association that crowdsources live air traffic control data broadcast by aircraft, which has been widely used for academic research. The demand for real-time and historical aircraft flight data has increased significantly during the COVID-19 outbreak.
EARTH SYSTEM SCIENCE DATA
(2021)
Article
Computer Science, Artificial Intelligence
Qiuyang Huang, Yongjian Yang, Yuanbo Xu, Funing Yang, Zhilu Yuan, Yongxiong Sun
Summary: Mobile signaling data has great value for urban traffic monitoring, improving coverage and accuracy.
Article
Computer Science, Information Systems
Yong Liu, Huaxi Gu, Ning Wang
Summary: The article proposes a high-performance and scalable traffic optimization strategy (HPSTOS) based on a hybrid approach that leverages the advantages of both centralized and distributed mechanisms. HPSTOS improves the efficiency of elephant flow detection through sampling and flow-table identification, guarantees preferential transmission of mice flows using priority scheduling, and schedules elephant flows by cost-aware dynamic flow scheduling on a centralized controller to improve their throughput. Evaluations show that HPSTOS outperforms existing schemes by realizing efficient elephant flow detection and improving network performance and scalability.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Telecommunications
Mengkun Wu, He Huang, Yu-E Sun, Yang Du, Shigang Chen, Guoju Gao
Summary: The paper proposes an efficient solution for finding the top-k elephant flows, reducing memory usage while ensuring high accuracy. By using two-mode active counter to record flow sizes and introducing dynamically exponential decay, the method achieves higher precision in expelling small flows while holding onto large ones.
IEEE COMMUNICATIONS LETTERS
(2021)
Article
Multidisciplinary Sciences
Natalia Gomez-Navarro, Julija Maldutyte, Kristina Poljak, Sew-Yeu Peak-Chew, Jonathon Orme, Brittany J. Bisnett, Caitlin H. Lamb, Michael Boyce, Davide Gianni, Elizabeth A. Miller
Summary: This study explores the possibility of selectively inhibiting protein secretion by perturbing protein-protein interactions involved in capture into transport vesicles. The researchers discovered a specific small molecule that can disrupt the function of the SEC24 protein, leading to decreased secretion of specific proteins.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Computer Science, Information Systems
Endra Joelianto, Muhammad Farhan Fathurrahman, Herman Yoseph Sutarto, Ivana Semanjski, Adiyana Putri, Sidharta Gautama
Summary: This paper investigates a data imputation method based on spatiotemporal PPCA, demonstrating the importance of constructing a spatial network for enhancing system robustness.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
Article
Computer Science, Artificial Intelligence
Robin Kuok Cheong Chan, Joanne Mun-Yee Lim, Rajendran Parthiban
Summary: The study proposed three solutions including real-time traffic simulation, pheromone and neural network traffic prediction and rerouting system, and weighted historical data method. Benchmark tests were conducted using Google Maps system, showing significant improvements in traffic management efficiency with the proposed systems.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Shohei Kamamura, Yuhei Hayashi, Yuki Miyoshi, Takeaki Nishioka, Chiharu Morioka, Hiroyuki Ohnishi
Summary: This paper proposes Fast xFlow Proxy, a fast and scalable traffic monitoring system that can handle various packet processing operations at a wire rate. It has been successfully tested on a large carrier network for practical monitoring.
IEICE TRANSACTIONS ON COMMUNICATIONS
(2022)
Article
Environmental Sciences
Haiqiang Yang, Xinming Zhang, Zihan Li, Jianxun Cui
Summary: This paper proposes a new deep learning model named TmS-GCN for region-level traffic prediction. The model utilizes GPS data for data-driven prediction, considering both spatial dependence among regions and the dynamic change of traffic within regions. Experimental results show that the proposed model outperforms both traditional time series prediction models and deep learning models at different scales.
Editorial Material
Engineering, Electrical & Electronic
Maurizio Dusi, Alessandro Finamore, Kimberly Claffy, Nevil Brownlee, Darryl Veitch
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2016)
Editorial Material
Computer Science, Information Systems
Ramin Sadre, Anna Sperotto, Nevil Brownlee, Rick Hofstede
INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT
(2013)
Editorial Material
Computer Science, Information Systems
Ramin Sadre, Anna Sperotto, Rick Hofstede, Nevil Brownlee
INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT
(2014)
Proceedings Paper
Computer Science, Theory & Methods
Maziar Janbeglou, Nevil Brownlee
IEEE 30TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS WORKSHOPS (WAINA 2016)
(2016)
Proceedings Paper
Computer Science, Information Systems
Se-young Yu, Nevil Brownlee, Aniket Mahanti
40TH ANNUAL IEEE CONFERENCE ON LOCAL COMPUTER NETWORKS (LCN 2015)
(2015)
Proceedings Paper
Telecommunications
Thitipong Jarassriwilai, Tiffany Dauber, Nevil Brownlee, Aniket Mahanti
2015 IEEE 40TH LOCAL COMPUTER NETWORKS CONFERENCE WORKSHOPS (LCN WORKSHOPS)
(2015)
Proceedings Paper
Computer Science, Hardware & Architecture
Maziar Janbeglou, Habib Naderi, Nevil Brownlee
2014 28TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS WORKSHOPS (WAINA)
(2014)
Proceedings Paper
Computer Science, Information Systems
Brian Trammell, David Gugelmann, Nevil Brownlee
TRAFFIC MONITORING AND ANALYSIS, TMA 2014
(2014)
Article
Engineering, Electrical & Electronic
N Brownlee, KC Claffy
IEEE COMMUNICATIONS MAGAZINE
(2002)
Article
Engineering, Electrical & Electronic
N Brownlee, R Fulton
IEEE COMMUNICATIONS MAGAZINE
(2000)
