2015 | OriginalPaper | Buchkapitel
Quantifying Competitiveness in Paging with Locality of Reference
verfasst von : Susanne Albers, Dario Frascaria
Erschienen in: Automata, Languages, and Programming
Verlag: Springer Berlin Heidelberg
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The classical paging problem is to maintain a two-level memory system so that a sequence of requests to memory pages can be served with a small number of faults. Standard competitive analysis gives overly pessimistic results as it ignores the fact that real-world input sequences exhibit locality of reference. In this paper we study the paging problem using an intuitive and simple locality model that records inter-request distances in the input. A characteristic vector
$$\mathcal{C}$$
C
defines a class of request sequences that satisfy certain properties on these distances. The concept was introduced by Panagiotou and Souza [
19
].
As a main contribution we develop new and improved bounds on the performance of important paging algorithms. A strength and novelty of the results is that they express algorithm performance in terms of locality parameters. In a first step we develop a new lower bound on the number of page faults incurred by an optimal offline algorithm
opt
. The bound is tight up to a small additive constant. Based on these expressions for
opt
’s cost, we obtain nearly tight upper and lower bounds on
lru
’s competitiveness, given any characteristic vector
$$\mathcal{C}$$
C
. The resulting ratios range between 1 and
$$k$$
k
, depending on
$$\mathcal{C}$$
C
. Furthermore, we compare
lru
to
fifo
and
fwf
. For the first time we show bounds that quantify the difference between
lru
’s performance and that of the other two strategies. The results imply that
lru
is strictly superior on inputs with a high degree of locality of reference. In particular, there exist general input families for which
lru
achieves constant competitive ratios whereas the guarantees of
fifo
and
fwf
tend to
$$k$$
k
, the size of the fast memory. Finally, we report on an experimental study that demonstrates that our theoretical bounds are very close to the experimentally observed ones. Hence we believe that our contributions bring competitive paging again closer to practice.