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Cost-Based Cache (CBC): An adaptive cache replacement strategy for Information-Centric Networks

algorithms-and-analysis-of-algorithms
computer-networks-and-communications
distributed-and-parallel-computing
optimization-theory-and-computation
internet-of-things

Abstract

Background. The escalating demand for digital content is placing unprecedented strain on network infrastructure, highlighting the critical need for efficient content delivery mechanisms like Information-Centric Network (ICN). Within ICN, in-network caching significantly improves content distribution; however, existing cache replacement techniques often struggle with dynamic network conditions and limited cache capacity that leading to suboptimal performance. This research addresses these limitations by proposing a novel Cost-Based Cache (CBC) replacement strategy designed to dynamically optimize caching decisions.

Methods. The proposed CBC technique integrates multiple factors, including content popularity such as frequency and recency, retrieval cost based on the link distance, and content freshness into a unified cost-based decision model for prioritized cache evictions. To manage cached content efficiently, CBC employs a dual-queue system (PRIMARY_QUEUE and SECONDARY_QUEUE) where entries are dynamically managed based on their calculated cost values. The technique was implemented and thoroughly evaluated using ndnSIM, a widely used ICN simulation framework. Simulations were conducted across both a controlled 5x5 Grid topology and the complex, real-world inspired Abilene topology using varying Content Store (CS) sizes. Key performance metrics, including Cache Hit Rate (CHR), Cache Miss Rate (CMR), and average retrieval delay, were examined and compared against traditional policies (FIFO, LRU) and hybrid approaches (LRFU, PFR).

Results. The simulation results demonstrate the consistent superiority of CBC. In the 5x5 Grid topology, CBC achieved substantial improvements in CHR, increasing from 13.4% (at CS size 10) to 46.1% (at CS size 50), which outperforms LRFU (max 32.6%), PFR (max 28.6%), LRU (max 28.9%), and FIFO (max 27.3%). Similarly, in the Abilene topology, CBC's CHR increases from 21.1% (at CS size 100) to 58.0% (at CS size 500), surpassing LRFU (max 52.2%), LRU (max 52.1%), and PFR/FIFO (max 50.0%). Correspondingly, CBC exhibited the lowest CMR and average retrieval delays across all scenarios, indicating enhanced cache utilization and reduced network overhead.

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