Enhancing Performance in Cloud Networks with Scrabble: Implementing an Adaptive Fine-Grained Cache and Merged Block Strategy

Abstract

In the evolving landscape of cloud computing, performance optimization remains a critical challenge. This paper presents an innovative approach designed to enhance cloud network performance through the implementation of an adaptive fine-grained cache and merged block strategy. Scrabble dynamically adjusts cache sizes and merges blocks based on real-time workload characteristics and access patterns. This adaptive mechanism ensures efficient utilization of resources, minimizes latency, and improves data retrieval speeds. The proposed strategy is evaluated through extensive simulations, demonstrating significant improvements in performance metrics such as response time, throughput, and cache hit ratio. The results underline the potential of Scrabble to provide a scalable and efficient solution for performance enhancement in diverse cloud environments.