Minimizing cache usage in paging

Abstract

Traditional paging models seek algorithms that maximize their performance while using the maximum amount of cache resources available. However, in many applications this resource is shared or its usage involves a cost. In this work we introduce the Minimum Cache Usage problem, which is an extension to the classic paging problem that accounts for the efficient use of cache resources by paging algorithms. In this problem, the cost of a paging algorithm is a combination of both its number of faults and the amount of cache it uses, where the relative cost of faults and cache usage can vary with the application. We present a simple family of online paging algorithms that adapt to the ratio between cache and fault costs, achieving competitive ratios that vary with, and that are between 2 and the cache size k. Furthermore, for sequences with high locality of reference, we show that the competitive ratio is at most 2, and provide evidence of the competitiveness of our algorithms on real world traces. Finally, we show that the offline problem admits a polynomial time algorithm. In doing so, we define a reduction of paging with cache usage to weighted interval scheduling on identical machines.