AbstractThis paper studies two methods for improving the competitive efficiency of on-line paging algorithms: in the first, the on-line algorithm can use more pages; in the second, it is allowed to have a lookahead, or in other words, some partial knowledge of the future. The paper considers a new measure for the lookahead size as well as Young's resource-bounded lookahead and proves that both measures have the attractive property that the competitive efficiency of an on-line algorithm with k extra pages and lookahead l depends on k + l. Hence, under these measures, an on-line algorithm has the same benefit from using an extra page or knowing an extra bit of the future
In evaluating an algorithm, worst-case analysis can be overly pessimistic. Average-case analysis can...
We construct an online algorithm for paging that achieves an O(r+log k) competitive ratio when compa...
The Multi-threaded Paging problem (MTP) was introduced as a generalization of Paging for the case wh...
This paper studies two methods for improving the competitive efficiency of on-line paging algorithms...
We introduce a new model of lookahead for on-line paging algorithms and study several algorithms usi...
In the competitive analysis of on-line problems, an on-line algorithm is presented with a sequence o...
AbstractMotivated by the fact that competitive analysis yields too pessimistic results when applied ...
Paging is one of the most prominent problems in the field of online algorithms. We have to serve a s...
The paging problem is that of deciding which pages to keep in a memory of k pages in order to minimi...
Paging is one of the prominent problems in the field of on-line algorithms. While in the determinist...
AbstractIn this paper, we give a finer separation of several known paging algorithms using a new tec...
AbstractThe paging problem is defined as follows: we are given a two-level memory system, in which o...
We consider existing research methodology for dealing with competitiveness analysis of on-line algor...
We study the writeback-aware caching problem, a variant of classic paging where paging requests that...
AbstractWe study the usefulness of lookahead in on-line server routing problems: if an on-line algor...
In evaluating an algorithm, worst-case analysis can be overly pessimistic. Average-case analysis can...
We construct an online algorithm for paging that achieves an O(r+log k) competitive ratio when compa...
The Multi-threaded Paging problem (MTP) was introduced as a generalization of Paging for the case wh...
This paper studies two methods for improving the competitive efficiency of on-line paging algorithms...
We introduce a new model of lookahead for on-line paging algorithms and study several algorithms usi...
In the competitive analysis of on-line problems, an on-line algorithm is presented with a sequence o...
AbstractMotivated by the fact that competitive analysis yields too pessimistic results when applied ...
Paging is one of the most prominent problems in the field of online algorithms. We have to serve a s...
The paging problem is that of deciding which pages to keep in a memory of k pages in order to minimi...
Paging is one of the prominent problems in the field of on-line algorithms. While in the determinist...
AbstractIn this paper, we give a finer separation of several known paging algorithms using a new tec...
AbstractThe paging problem is defined as follows: we are given a two-level memory system, in which o...
We consider existing research methodology for dealing with competitiveness analysis of on-line algor...
We study the writeback-aware caching problem, a variant of classic paging where paging requests that...
AbstractWe study the usefulness of lookahead in on-line server routing problems: if an on-line algor...
In evaluating an algorithm, worst-case analysis can be overly pessimistic. Average-case analysis can...
We construct an online algorithm for paging that achieves an O(r+log k) competitive ratio when compa...
The Multi-threaded Paging problem (MTP) was introduced as a generalization of Paging for the case wh...