The traffic bandwidth costs, primarily driven by outbound traffic, comprise a significant amount of operating expenditure in CDNs, induced by the traffic from the end-users to edge servers (edge cost) and from the edge to the center servers (midgress cost). Traffic allocation is the main approach to minimizing the total bandwidth cost. The joint optimization of the total costs is challenging, specifically when the percentile charging mechanism as well as some other practical issues are considered, such as the dynamicity of midgress traffic and the granularity of traffic allocation. In this work, based on our novel miss ratio prediction mechanism, we propose the first online framework, namedIris, jointly optimizing the edge and midgress costs under the 95th percentile charging in commercial CDNs.Iriscan theoretically achieve a competitive ratio of$1+\frac {p_{e}}{\beta \cdot p_{c}}$, when the miss ratio of all domains is set as$\beta $. Here$p_{e}$and$p_{c}$are the unit bandwidth price of the edge and midgress cost, respectively.Irisis tolerant to prediction errors which can be deployed in practical CDN systems. Extensive experiments based on real data indicate thatIriscan dramatically reduce bandwidth costs by about 8.149% compared with the SOTA schemes, potentially saving millions of dollars per month for our large-scale commercial CDN collaborator.

With the rapid growth of data-intensive applications, such as artificial intelligence and the Internet of Things, CDNs, which use persistent storage (e.g., SSDs and HDDs) to cache data at the edge, have become crucial for enhancing network efficiency. Two metrics—hit ratio and processing la tency—are essential for evaluating CDN caching performance. However, CDN caching faces the challenge of write amplification, creating a trade-off between random access for higher hit ratios and sequential writes for reducing processing latency. Existing cache designs struggle to effectively balance these conflicting requirements across diverse workloads. In this paper, we present FOSS, a caching system specifically optimized for CDNs deployed on SSD-based storage and hybrid SSD–HDD storage, which features a streamlined, thin file system that operates independently of the kernel. At its heart, FOSS employs a multi-level FIFO queue to strike a balance between local sequential and global random access on SSDs. Then, FOSS incorporates a learning-based method to dynamically configure the multi-level structure configuration, making the system adaptive to various workload characteristics and caching algorithm requirements. Therefore, FOSS ensures better performance across different scenarios. Our extensive experiments show FOSS improves hit ratios significantly over existing systems, reduces end-to-end response latency by 16.5% and demonstrates a consistent performance improvement in various settings on large-scale commercial CDN traces.

The traffic bandwidth costs comprise a significant amount of operating expenditure in CDNs, induced by the traffic from the end-users to edge servers (edge cost) and from the edge to the center servers (midgress cost). Traffic allocation is the main approach to minimizing the total bandwidth cost. The joint optimization of the total costs is challenging, specifically when the percentile charging mechanism as well as some other practical issues are considered, such as the dynamicity of midgress traffic and the granularity of traffic allocation. In this work, based on our novel miss ratio prediction mechanism, we propose the first online framework, named Iris, jointly optimizing the edge and midgress costs under the 95th percentile charging in commercial CDNs. Iris can theoretically achieve a competitive ratio of$1+\frac{p_{e}}{\beta\cdot p_{c}}$, when the miss ratio of all domains is set as$\beta$. Here$p_{e}$and$p_{c}$are the unit bandwidth price of the edge and midgress cost, respectively. Iris is tolerant to prediction errors which can be deployed in practical CDN systems. Extensive experiments based on real data indicate that Iris can dramatically reduce bandwidth costs by about 8.149% compared with the SOTA schemes, potentially saving millions of dollars per month for our large-scale commercial CDN collaborator.