Characterizing JSON Traffic Patterns on a CDN

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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Index Terms

• Networks

  • Network performance evaluation

    • Network measurement