  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.
