Network Traffic Analysis as a Strategy for Cache Management

Abstract

Given the significant revolution in data and technology and the increasing need to optimize system performance, it is imperative to transition towards unconventional caching methodologies in the context of contemporary technologies such as AI, edge computing, heterogeneous IoT, big data, and 5G mobile networks. This research paper presents a novel methodology for cache writing, wherein network traffic is carefully analyzed and examined, and data is categorized as highly accessed utilizing the probability distribution of a bell curve. The proposed approach focuses on analyzing network traffic and selectively writing data into the cache, unlike the old approach, which ignored network traffic and randomly added data into the cache. Empirical findings demonstrate favorable performance outcomes in comparison to conventional techniques, namely LIFO, FIFO, LRU, LFU, MFU, and MRU.