Network Measurement and Performance Analysis at Server Side

Guang-Qian Peng, Guangtao Xue and Yi-Chao Chen
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Guang-Qian Peng: Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Guangtao Xue: Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Yi-Chao Chen: Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Future Internet, 2018, vol. 10, issue 7, 1-18

Abstract: Network performance diagnostics is an important topic that has been studied since the Internet was invented. However, it remains a challenging task, while the network evolves and becomes more and more complicated over time. One of the main challenges is that all network components (e.g., senders, receivers, and relay nodes) make decision based only on local information and they are all likely to be performance bottlenecks. Although Software Defined Networking (SDN) proposes to embrace a centralize network intelligence for a better control, the cost to collect complete network states in packet level is not affordable in terms of collection latency, bandwidth, and processing power. With the emergence of the new types of networks (e.g., Internet of Everything, Mission-Critical Control, data-intensive mobile apps, etc.), the network demands are getting more diverse. It is critical to provide finer granularity and real-time diagnostics to serve various demands. In this paper, we present EVA, a network performance analysis tool that guides developers and network operators to fix problems in a timely manner. EVA passively collects packet traces near the server (hypervisor, NIC, or top-of-rack switch), and pinpoints the location of the performance bottleneck (sender, network, or receiver). EVA works without detailed knowledge of application or network stack and is therefore easy to deploy. We use three types of real-world network datasets and perform trace-driven experiments to demonstrate EVA’s accuracy and generality. We also present the problems observed in these datasets by applying EVA.

Keywords: network measurement; network performance problem; TCP congestion control (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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