How Edge Computing and Initial Congestion Window Affect Latency of Web-Based Services: Early Experiences with Baidu?

Qingyang Zhang, Hong Zhong, Jiaoren Wu, Weisong Shi
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引用次数: 5

Abstract

More and more things, generating huge data, will come into and enrich our lives, and the Web of Things (WoT) as a guide allows these things to be part of the World Wide Web (WWW), by using various data analysis services on the WWW. However, based on our observation on the image recognition and searching service of Baidu, pure image data transmission costs hundreds of milliseconds, besides the time of connection establishment. Inspired by the emerging Edge Computing, we analyzed the relationship between time consumption and different service provider's locations, as well as different initial congestion windows of the Transmission Control Protocol (TCP), which affect web-based services' performance. Based on our experiments in different scenarios (i.e., initial congestion window, speed of connection device and server location), we found that pushing services to the edge of network and increasing initial congestion window, both of them can reduce latency on connection establishment and data transmission, especially when users are traveling at a high speed.
边缘计算和初始拥塞窗口如何影响web服务的延迟:百度的早期经验?
越来越多的事物,产生巨大的数据,将进入并丰富我们的生活,而物联网(WoT)作为指南,通过使用万维网上的各种数据分析服务,使这些事物成为万维网(WWW)的一部分。然而,根据我们对百度的图像识别和搜索服务的观察,除了建立连接的时间外,纯图像数据传输需要数百毫秒的时间。受新兴边缘计算的启发,我们分析了时间消耗与不同服务提供商位置之间的关系,以及传输控制协议(TCP)的不同初始拥塞窗口,这影响了基于web的服务性能。通过对不同场景(即初始拥塞窗口、连接设备速度和服务器位置)的实验,我们发现将业务推到网络边缘和增加初始拥塞窗口都可以减少连接建立和数据传输的延迟,特别是当用户高速旅行时。
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