4.7 Article

Online detection of pathological TCP flows with retransmissions in high-speed networks

期刊

COMPUTER COMMUNICATIONS
卷 127, 期 -, 页码 95-104

出版社

ELSEVIER
DOI: 10.1016/j.comcom.2018.06.002

关键词

Network management; Performance monitoring; Quality of Service; TCP retransmissions; TCP modeling

资金

  1. Spanish Ministry of Economy and Competitiveness
  2. European Regional Development Fund under the project TRAFICA [MINECO / FEDER TEC2015-69417-C2-1-R]
  3. European Regional Development Fund under the project Preproceso Inteligente de Trafico [MINECO / FEDER TEC2015-69417-C2-2-R]
  4. European Regional Development Fund under the project RACING DRONES [MINECO / FEDER RTC-2016-4744-7]
  5. Spanish Ministry of Education, Culture and Sport

向作者/读者索取更多资源

Online Quality of Service (QoS) assessment in high speed networks is one of the key concerns for service providers, namely to detect QoS degradation on-the-fly as soon as possible and avoid customers' complaints. In this regard, a Key Performance Indicator (KPI) is the number of TCP retransmissions per flow, which is related to packet losses or increased network and/or client/server latency. However, to accurately detect TCP retransmissions the whole sequence number list should be tracked which is a challenging task in multi-Gb/s networks. In this paper we show that the simplest approach of counting as a retransmission a packet whose sequence number is smaller than the previous one is enough to detect pathological flows with severe retransmissions. Such a lightweight approach eliminates the need of tracking the whole TCP flow history, which severely restricts traffic analysis throughput. Our findings show that low False Positive Rates (FPR) and False Negative Rates (FNR) can be achieved in the detection of such pathological flows with severe retransmissions, which are of paramount importance for QoS monitoring. Most importantly, we show that live detection of such pathological flows at 10 Gb/s rate per processing core is feasible.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据