Comparative Analysis of Distributed Caching Algorithms: Performance Metrics and Implementation Considerations
Year: 2025
Type: preprint
Abstract: This paper presents a comprehensive comparison of distributed caching algorithms employed in modern distributed systems. We evaluate various caching strategies including Least Recently Used (LRU), Least Frequently Used (LFU), Adaptive Replacement Cache (ARC), and Time-Aware Least Recently Used (TLRU) against metrics such as hit ratio, latency reduction, memory overhead, and scalability. Our analysis reveals that while traditional algorithms like LRU remain prevalent, hybrid approaches incorporating machine learning techniques demonstrate superior performance in dynamic environments. Additionally, we analyze implementation patterns across different distributed architectures and provide recommendations for algorithm selection based on specific workload characteristics.
Source: arXiv (Cornell University)
Authors: Mayer, Helen, Richards, James
Language: English
Topic: Caching and Content Delivery
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4409696912