It is well known that competitive analysis yields too pessimistic re-sults when applied to the paging problem and it also cannot make a distinction between many paging strategies. Many deterministic paging algorithms achieve the same competitive ratio, ranging from inefficient strategies as flush-when-full to the good performing least-recently-used (LRU). In this paper, we study this fundamental online problem from the viewpoint of stochastic dominance. We show that when sequences are drawn from distributions modelling locality of reference, LRU is stochastically better than any other online paging algorithm
AbstractIn this paper, we give a finer separation of several known paging algorithms using a new tec...
Paging is one of the prominent problems in the field of on-line algorithms. While in the determinist...
We introduce a new model of lookahead for on-line paging algorithms and study several algorithms usi...
In evaluating an algorithm, worst-case analysis can be overly pessimistic. Average-case analysis can...
In this paper we explore the effects of locality on the performance of paging algorithms. Traditiona...
It has been experimentally observed that LRU and variants thereof are the preferred strategies for o...
It has been experimentally observed that LRU and variants thereof are the preferred strategies for ...
AbstractMotivated by the fact that competitive analysis yields too pessimistic results when applied ...
AbstractThe Sleator-Tarjan competitive analysis of paging (Comm. ACM28 (1985), 202-208) gives us the...
We present a competitive analysis of the LRFU paging algorithm, a hybrid of the LRU (Least Recently...
AbstractThe relative worst-order ratio, a relatively new measure for the quality of on-line algorith...
AbstractThe paging problem is defined as follows: we are given a two-level memory system, in which o...
The paging problem is defined as follows: we are given a two-level memory system, in which one level...
Recall our three goals for the mathematical analysis of algorithms — the Explanation Goal, the Compa...
International audienceStochastic dominance is a technique for evaluating the performance of online a...
AbstractIn this paper, we give a finer separation of several known paging algorithms using a new tec...
Paging is one of the prominent problems in the field of on-line algorithms. While in the determinist...
We introduce a new model of lookahead for on-line paging algorithms and study several algorithms usi...
In evaluating an algorithm, worst-case analysis can be overly pessimistic. Average-case analysis can...
In this paper we explore the effects of locality on the performance of paging algorithms. Traditiona...
It has been experimentally observed that LRU and variants thereof are the preferred strategies for o...
It has been experimentally observed that LRU and variants thereof are the preferred strategies for ...
AbstractMotivated by the fact that competitive analysis yields too pessimistic results when applied ...
AbstractThe Sleator-Tarjan competitive analysis of paging (Comm. ACM28 (1985), 202-208) gives us the...
We present a competitive analysis of the LRFU paging algorithm, a hybrid of the LRU (Least Recently...
AbstractThe relative worst-order ratio, a relatively new measure for the quality of on-line algorith...
AbstractThe paging problem is defined as follows: we are given a two-level memory system, in which o...
The paging problem is defined as follows: we are given a two-level memory system, in which one level...
Recall our three goals for the mathematical analysis of algorithms — the Explanation Goal, the Compa...
International audienceStochastic dominance is a technique for evaluating the performance of online a...
AbstractIn this paper, we give a finer separation of several known paging algorithms using a new tec...
Paging is one of the prominent problems in the field of on-line algorithms. While in the determinist...
We introduce a new model of lookahead for on-line paging algorithms and study several algorithms usi...