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Content delivery networks (CDNs) cache and deliver hundreds of trillions of user requests each day from hundreds of thousands of servers around the world. The traffic served by CDNs can be partitioned into hundreds of traffic classes, each with different user access patterns, popularity distributions, object sizes, and performance requirements. Midgress is the cache miss traffic between the CDN's servers and the content provider origins. A major goal of a CDN is to minimize its midgress, since higher midgress translates to higher bandwidth costs and increased user-perceived latency. We propose algorithms that provision traffic classes to servers such that midgress is minimized. Using extensive traces from Akamai's CDN, we show that our midgress-aware traffic provisioning schemes can reduce midgress by nearly 20% in comparison with the midgress-unaware schemes currently in use. We also propose an efficient heuristic for traffic provisioning that achieves near-optimal midgress and is suitable for use in production settings. Further, we show how our algorithms can be extended to other settings that require minimum caching performance per traffic class and minimum content duplication for fault tolerance. Finally, our paper provides a strong case for implementing midgress-aware traffic provisioning in production CDNs.
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This content will become publicly available on November 20, 2025
CDN-Shifter: Leveraging Spatial Workload Shifting to Decarbonize Content Delivery Networks
Content Delivery Networks (CDNs) are Internet-scale systems that deliver streaming and web content to users from many geographically distributed edge data centers. Since large CDNs can comprise hundreds of thousands of servers deployed in thousands of global data centers, they can consume a large amount of energy for their operations and thus are responsible for large amounts of Green House Gas (GHG) emissions. As these networks scale to cope with increased demand for bandwidth-intensive content, their emissions are expected to rise further, making sustainable design and operation an important goal for the future. Since different geographic regions vary in the carbon intensity and cost of their electricity supply, in this paper, we consider spatial shifting as a key technique to jointly optimize the carbon emissions and energy costs of a CDN. We present two forms of shifting: spatial load shifting, which operates within the time scale of minutes, and VM capacity shifting, which operates at a coarse time scale of days or weeks. The proposed techniques jointly reduce carbon and electricity costs while considering the performance impact of increased request latency from such optimizations. Using real-world traces from a large CDN and carbon intensity and energy prices data from electric grids in different regions, we show that increasing the latency by 60ms can reduce carbon emissions by up to 35.5%, 78.6%, and 61.7% across the US, Europe, and worldwide, respectively. In addition, we show that capacity shifting can increase carbon savings by up to 61.2%. Finally, we analyze the benefits of spatial shifting and show that it increases carbon savings from added solar energy by 68% and 130% in the US and Europe, respectively.
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- PAR ID:
- 10591368
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400712869
- Page Range / eLocation ID:
- 505 to 521
- Format(s):
- Medium: X
- Location:
- Redmond WA USA
- Sponsoring Org:
- National Science Foundation
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