PackCache: An Online Cost-driven Data Caching Algorithm in the Cloud

TL;DR

PackCache is an online cloud data caching algorithm that efficiently packs co-utilised data items to reduce transfer costs, leveraging FP-Tree mining and anticipatory caching for improved performance.

Contribution

The paper introduces PackCache, a novel online caching algorithm that uses FP-Tree mining and anticipatory caching to optimize data transfer costs in cloud environments.

Findings

Achieves a 2α competitive ratio, matching the lower bound for deterministic algorithms.

Proven to be time and space efficient for online request serving.

Experimental results demonstrate cost-effectiveness and scalability.

Abstract

In this paper, we study a data caching problem in the cloud environment, where multiple frequently co-utilised data items could be packed as a single item being transferred to serve a sequence of data requests dynamically with reduced cost. To this end, we propose an online algorithm with respect to a homogeneous cost model, called PackCache, that can leverage the FP-Tree technique to mine those frequently co-utilised data items for packing whereby the incoming requests could be cost-effectively served online by exploiting the concept of anticipatory caching. We show the algorithm is 2\alpha competitive, reaching the lower bound of the competitive ratio for any deterministic online algorithm on the studied caching problem, and also time and space efficient to serve the requests. Finally, we evaluate the performance of the algorithm via experimental studies to show its actual cost-effectiveness and scalability.