Sub-query Fragmentation for Query Analysis and Data Caching in the Distributed Environment

TL;DR

This paper proposes an adaptive distributed data caching framework that optimizes data chunk placement across geographically distributed caches to reduce data transfer costs.

Contribution

It introduces a novel method for identifying and moving data chunks in a distributed environment to improve cache efficiency and reduce network load.

Findings

Effective data chunk identification for caching

Reduced data transfer through optimized cache placement

Adaptive framework improves cache performance

Abstract

When data stores and users are distributed geographically, it is essential to organize distributed data cache points at ideal locations to minimize data transfers. To answer this, we are developing an adaptive distributed data caching framework that can identify suitable data chunks to cache and move across a network of community cache locations.