Fast-Response Edge Caching Scheme for Graph Data

By deploying distributed storage space on edge servers, mobile edge networks significantly enhance computation and transmission efficiency for wireless tasks. The selection of an appropriate caching policy not only optimizes bandwidth utilization but also alleviates network congestion. Given the intricate connectivity and vast data volume in edge computing, coupled with users’ demand for rapid response times, proposing a cache solution that closely matches data attributes becomes imperative to enhance overall efficiency. In this paper, we introduce RECG, a high-speed edge caching scheme designed specifically for graph data, leveraging the intricate data connectivity. RECG generates query graphs from edge servers to ensure swift and accurate identification of popular nodes. Additionally, we introduce a rapid hot-spot propagation partitioning technique to optimize the partitioning process, increasing the hit rate of partitioned subgraphs in the cache while reducing runtime. Our experimental evaluation, conducted on real-world datasets, compares RECG with specialized edge caching graph partitioning algorithms such as LGPE and other baseline algorithms. The thorough experimental results demonstrate the advantages of the proposed algorithm in terms of cache hit rate and processing delay.