Characterizing JSON Traffic Patterns on a CDN

Santiago Vargas, U. Goel, Moritz Steiner, A. Balasubramanian
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引用次数: 5

Abstract

Content delivery networks serve a major fraction of the Internet traffic, and their geographically deployed infrastructure makes them a good vantage point to observe traffic access patterns. We perform a large-scale investigation to characterize Web traffic patterns observed from a major CDN infrastructure. Specifically, we discover that responses with application/json content-type form a growing majority of all HTTP requests. As a result, we seek to understand what types of devices and applications are requesting JSON objects and explore opportunities to optimize CDN delivery of JSON traffic. Our study shows that mobile applications account for at least 52% of JSON traffic on the CDN and embedded devices account for another 12% of all JSON traffic. We also find that more than 55% of JSON traffic on the CDN is uncacheable, showing that a large portion of JSON traffic on the CDN is dynamic. By further looking at patterns of periodicity in requests, we find that 6.3% of JSON traffic is periodically requested and reflects the use of (partially) autonomous software systems, IoT devices, and other kinds of machine-to-machine communication. Finally, we explore dependencies in JSON traffic through the lens of ngram models and find that these models can capture patterns between subsequent requests. We can potentially leverage this to prefetch requests, improving the cache hit ratio.
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在CDN上表征JSON流量模式
内容交付网络服务于Internet流量的主要部分,其地理上部署的基础设施使其成为观察流量访问模式的良好有利位置。我们进行了大规模的调查,以表征从主要CDN基础设施观察到的Web流量模式。具体来说,我们发现application/json内容类型的响应在所有HTTP请求中占越来越大的比例。因此,我们试图了解哪些类型的设备和应用程序正在请求JSON对象,并探索优化JSON流量的CDN交付的机会。我们的研究表明,移动应用程序占CDN上JSON流量的至少52%,嵌入式设备占所有JSON流量的另外12%。我们还发现CDN上超过55%的JSON流量是不可缓存的,这表明CDN上很大一部分JSON流量是动态的。通过进一步观察请求的周期性模式,我们发现6.3%的JSON流量是周期性请求的,这反映了(部分)自主软件系统、物联网设备和其他类型的机器对机器通信的使用。最后,我们通过ngram模型探索JSON流量中的依赖关系,并发现这些模型可以捕获后续请求之间的模式。我们可以潜在地利用这一点来预取请求,提高缓存命中率。
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