Smart Cache Insertion and Promotion Policy for Content Delivery Networks

Improving hit rates can be achieved by enhancing cache replacement algorithms with the identification of zero-reuse objects (ZROs) and inserting them at the end of the cache queue. Note that the promotion policy needs to achieve a similar task as the above insertion policy since the hit object may immediately become a ZRO (called P-ZRO) that is not suitable for placement at the front of the queue. However, existing studies have yet to consider P-ZROs, and current insertion algorithms struggle to simultaneously identify both ZROs and P-ZROs. To address these issues, we propose integrating the insertion and promotion policies. We do this by treating hit objects as special missing objects and employing reinforcement learning to create a unified model for both policies, where the learning function recognizes the relationship between performance changes and the emergence of ZROs and P-ZROs. Our proposed solution is a smart cache insertion and promotion policy (SCIP) that dynamically adjusts the insertion position using a bimodal insertion policy for both missing and hit objects, guided by the model. Extensive experiments demonstrate that SCIP significantly improves overall performance in real-world content delivery network systems and outperforms state-of-the-art insertion policies in terms of miss ratios in the simulator. In addition, deploying SCIP on optimal cache replacement algorithms can further decrease their miss ratios.