## 1 Introduction  
In next-generation network architectures such as Information-Centric Networking (ICN), in-network caching is one of the core functions to achieve efficient content distribution [1, 2, 3, 4]. ICN uses location-independent names to uniquely identify each piece of content and replaces traditional security mechanisms that rely on communication channel protection with content-based security [5], which achieves complete separation of content and its location. This enables the network layer to transparently cache content and efficiently serve subsequent requests: users can directly retrieve data from nearby nodes with cached content replicas using the content's name, without having to access the original server. This significantly reduces network connection demands, minimizes redundant traffic and bandwidth consumption, and effectively optimizes end-to-end latency performance [6, 7]. To achieve large-scale deployment of ICN caching, the primary challenge lies in the design and implementation of cache nodes. Since caching operations in ICN are closely coupled with the forwarding pipeline, the I/O rate of the caching system must meet strict performance requirements to match the forwarding rate of network components [8]. For instance, high-speed memory (such as DRAM) is typically used to enable line-speed caching operations, but it has limitations in terms of cost and cache capacity. In the context of large-scale Internet traffic, the effectiveness of ICN in-network caching depends largely on the ability to provide sufficient cache capacity to host a large number of content replicas [9], thereby improving the cache hit rate. Persistent storage devices such as SSDs (Solid-State Drives), with their lower upfront costs and higher storage capacities, can offer scalability at the terabyte (TB) level for ICN caching. However, high access latency remains a major limitation to their widespread application in ICN cache nodes. In this context, researchers have begun exploring the use of multiple storage technologies to construct hierarchical cache architectures in order to address the trade-offs between cache capacity, deployment costs, and read/write speed [8]. A typical approach is to use SSDs as an additional cache layer to DRAM [9; 10; 11], where the core idea is to store a small amount of popular data in DRAM to fully utilize its high-speed memory bandwidth, while storing less popular data in SSDs to leverage their large storage capacity. At the same time, DRAM is used to store indexes and act as a write buffer for the SSD cache. In addition, related research has further optimized the access latency performance of hierarchical cache architectures by adopting techniques such as data prefetching [12] and decoupling caching from forwarding operations [13]. Cache management in hierarchical cache architectures remains an unresolved issue. Existing research typically handles local replica management within a single cache layer through cache replacement policies [14]. However, in hierarchical cache architectures, the differentiated read/write characteristics of various storage media present new challenges for replica management. For example, the limited lifespan of SSDs means that they can only endure a finite number of erase/write cycles, so unnecessary write operations should be avoided to reduce the operating costs of the cache system. Most existing studies filter data written to SSDs based on attributes like content popularity [15; 10], but they do not fully consider the characteristic information of the node and network dimensions in ICN, which leads to inefficient filtering or underutilization of SSD cache space. In addition, the key issue in cache management lies in designing cache replacement policies that can adapt to the characteristics of the hierarchical cache architecture. Due to the differences in cache load and request access patterns between the upper and lower layers, homogeneous cache management may lead to a decline in overall cache performance.