{"title":"SONAR: A scalable stream-oriented system for real-time network traffic measurements","authors":"Jun Liu, Y. Du, Jie Yang, N. Ansari","doi":"10.1109/HPSR.2015.7483101","DOIUrl":null,"url":null,"abstract":"Accurate and real-time network measurements are becoming increasingly critical for a large variety of management tasks like accounting, bandwidth provisioning and security analysis. However, existing network measurement techniques have major limitations in supporting scalable and real-time traffic data monitoring and analyzing on high-speed (10Gbps and beyond) network links. Therefore, we propose a novel real-time network measurement system, named SONAR, which facilitates the convergence of real-time network monitoring and traffic analysis. We illustrate how the proposed system is designed and implemented based on streaming computing technologies, and demonstrate its capabilities with a built-in abnormal traffic detection application. The proposed system, based on real-world actualization and evaluation, has been demonstrated to be a high-performance and scalable solution for real-time network traffic measurements.","PeriodicalId":360703,"journal":{"name":"2015 IEEE 16th International Conference on High Performance Switching and Routing (HPSR)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 16th International Conference on High Performance Switching and Routing (HPSR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPSR.2015.7483101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Accurate and real-time network measurements are becoming increasingly critical for a large variety of management tasks like accounting, bandwidth provisioning and security analysis. However, existing network measurement techniques have major limitations in supporting scalable and real-time traffic data monitoring and analyzing on high-speed (10Gbps and beyond) network links. Therefore, we propose a novel real-time network measurement system, named SONAR, which facilitates the convergence of real-time network monitoring and traffic analysis. We illustrate how the proposed system is designed and implemented based on streaming computing technologies, and demonstrate its capabilities with a built-in abnormal traffic detection application. The proposed system, based on real-world actualization and evaluation, has been demonstrated to be a high-performance and scalable solution for real-time network traffic measurements.