Elastic paging

We study a generalization of the classic paging problem where memory capacity can vary over time - a property of many modern computing realities, from cloud computing to multi-core and energy-optimized processors. We show that good performance in the "classic" case provides no performance guarantees when memory capacity fluctuates: roughly speaking, moving from static to dynamic capacity can mean the difference between optimality within a factor 2 in space, time and energy, and suboptimality by an arbitrarily large factor. Surprisingly, several classic paging algorithms still perform remarkably well, maintaining that factor 2 optimality even if faced with adversarial capacity fluctuations - without taking those fluctuations into explicit account!