Latency-Aware Edge Caching of Product Media via LSTM-Based Prefetch Algorithms
Keywords:
edge caching, LSTM, content delivery network, product media, prefetching, clickstream analytics, cache hit ratioAbstract
LSTM-based prefetching is employed in latency-optimized edge caching for high-traffic product media. Improve mobile e-commerce metrics. User click-stream data and real-time inventory events are used to predict SKU-level media asset demand. Image preloading to CDN edge nodes is sensible. This predictive technique optimises mobile conversion rates by increasing cache hit ratios and decreasing tail delay in first-contentful-paint (FCP) measures. Average FCP improvement was 150 milliseconds and 95th-percentile cache misses were 52% lower than baseline heuristic-based caching across fourteen Foot Locker stores globally. The CDN-compatible design doesn't need client-side acceleration. This helps retail multi-tenant scalability. This study improves latency-sensitive content distribution in changing retail environments for deep sequence modelling and edge computing.
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