Amos Fiat, Richard Karp, Mike Luby, Lyle McGeoch, Daniel Sleator, and Neal E. Young. Competitive paging algorithms. Journal of Algorithms, 12(4):685--699, December 1991. Home/Search Document Details and Download
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Scheduling and Resource Management Techniques for Multiprocessors - Black (1990) (25 citations) (Correct)
....is defined to be the average of its costs over all of the possible series of random choices. Competitiveness is defined as before, but it uses this modified definition of cost. For a number of different problems, it has been shown that the competitive factor can be reduced by the use of randomness [17, 27]. We have presented and analyzed new strongly competitive algorithms for replication and migration problems that arise in the management of distributed shared memory for multiprocessor systems. These algorithms are applicable to many existing and proposed multiprocessor architectures. The proofs ....
Amos Fiat, Richard Karp, Michael Luby, Lyle McGeoch, Daniel Sleator, and Neal Young. Competitive Paging Algorithms. Technical Report CMU-CS-86-164, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, 1986.
A Randomized Online Algorithm for Bandwidth Utilization - Arora, Brinkman (2002) (1 citation) (Correct)
....of ) than the deterministic algorithm. Furthermore, we show that this algorithm is optimal up to constant factors. Thus we provide a new problem in online algorithms in which randomized algorithms are provably better than deterministic algorithms. This has happened before, most notably in paging [3]. Another reason for interest in our work is that our algorithm is a randomized version of MIMD, thus suggesting that at least in the Karp et al. model, the optimum strategy for the hosts may con ict with the public good. Of course, we stress as Karp et al. did also that this model is simplistic ....
A. Fiat, R. Karp, M. Luby, L. McGeoch, D. Sleator, and N. Young. Competitive paging algorithms. Journal of Algorithms, 12(4):685-699, 1991.
A Randomized Online Algorithm for Bandwidth Utilization - Arora, Brinkman (2002) (1 citation) (Correct)
....of ) than the deterministic algorithm. Furthermore, we show that this algorithm is optimal up to constant factors. Thus we provide a new problem in online algorithms in which randomized algorithms are provably better than deterministic algorithms. This has happened before, most notably in paging [3]. Another reason for interest in our work is that our algorithm is a randomized version of MIMD, thus suggesting that at least in the Karp et al. model, the optimum strategy for the hosts may conflict with the public good. Of course, we stress as Karp et al. did also that this model is ....
A. Fiat, R. Karp, M. Luby, L. McGeoch, D. Sleator, and N. Young. Competitive paging algorithms. Journal of Algorithms, 12(4):685--699, 1991.
On-line Complexity of Monotone Set Systems (Extended Abstract) - Kaplan, Szegedy (Correct)
....of the ratio of the online and the optimal off line solutions, where the maximum is taken over all input sequences. This ratio, called by Sleator and Tarjan [13] the competitive ratio, has been used to analyze algorithms for various data structures, paging, caching, and graph problems (See e.g. [5, 12, 8, 6]) and gave rise to elegant generalizations, such as metrical task systems introduced by Borodin, Linial, and Saks [4] and the K server problems introduced by Manasse, McGeoch and Sleator [11] see also [9] Most on line models assume that there is small commonknowledge shared between the ....
A. Fiat, R. Karp, M. Luby, L. McGeoch, D. D. Sleator, and N. Young. Competitive paging algorithms. J. Algorithms, 12:685--699, 1991.
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....item can be processed by any of these stations. In this example, m is the maximum number of open files on a file server. Note that the multi service sorting buffer problem in which the sorting buffer has storage capacity for only one item is equivalent to the classical paging problem (see, e.g. [2, 10]) In the painting center of a car plant, a sequence of cars traverses the final layer painting where each car is painted with its own top coat. If two consecutive cars have to be painted in different colors then a color change is required. Such a color change causes cost due to the wastage of ....
A. Fiat, R. M. Karp., M. Luby, L. A. McGeoch, D. D. Sleator, and N. E. Young. Competitive paging algorithms. Journal of Algorithms, 12(2):685--699, 1991.
Random Walks on Weighted Graphs, and Applications.. - Coppersmith.. (1993) (24 citations) (Correct)
....previous moves, and the next cat move depends only on its current position. Some special cases of the cat and mouse game have been studied by Baeza Yates et al. 1] We show that this cat and mouse game is at the core of many other on line algorithms that have evoked tremendous interest of late [3, 4, 5, 8, 9, 11, 18, 20, 21, 22]. We consider two settings. The first is the k server problem, defined in [18] An on line algorithm manages k mobile servers located at the vertices of a graph G whose edges have positive real lengths; it has to satisfy on line a sequence of requests for service at vertex v i , i = 1; 2; ....
....to generate the requests adapting to the on line algorithm s moves, but to postpone its decisions on its server moves until the entire sequence of requests has been generated; this is an adaptive off line adversary. These three types of adversaries for randomized algorithms are provably different [3, 11, 21]. However, they all coincide when the on line algorithm is deterministic. Furthermore, if there is a randomized algorithm that is c competitive against adaptive on line adversaries, then there is a c competitive deterministic algorithm [3] The cache problem where we manage a fully ....
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A. Fiat, R. M. Karp, M. Luby, L. A. McGeoch, D. D. Sleator, and N. Young. Competitive paging algorithms. Journal of Algorithms, 12:685--699, 1991.
Random Walks on Weighted Graphs, and Applications.. - Coppersmith.. (1990) (24 citations) (Correct)
....finds the mouse. This strategy is very simple, and memoryless: the cat need not remember its previous moves, and the next cat move depends only on its current position. We show that this cat and mouse game is at the core of many other online algorithms that have evoked tremendous interest of late [2, 3, 4, 7, 8, 10, 14, 16, 17, 18]. We consider two settings. The first is the k server problem, defined in [14] An on line algorithm manages k mobile servers located at the nodes of a graph G whose edges have positive real lengths; it has to satisfy a sequence of requests for service at node v i , i = 1; 2; by moving a ....
....adversary. Alternatively, one can strengthen the adversary by allowing it to postpone its decision on its server moves until the entire sequence of requests has been generated; this is an adaptive off line adversary. These three types of adversaries for randomized algorithms are provably different [2, 10, 17]. However, they all coincide when the on line algorithm is deterministic. Furthermore, if there is a randomized algorithm that is c competitive against adaptive on line adversaries, then there is a c competitive deterministic algorithm [2] Theorem 5.1 Let C be a resistive cost matrix. Then ....
A. Fiat, R. M. Karp, M. Luby, L. A. McGeoch, D. D. Sleator, and N. Young. Competitive paging algorithms. Journal of Algorithms, 12:685--699, 1991. 20
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A. Fiat, R. M. Karp, M. Luby, L. A. McGeoch, D. D. Sleator, and N. E. Young. Competitive paging algorithms. Technical Report CMU-CS-88-196, School of Computer Science, Carnegie Mellon University, 1988. New version appeared in Journal of Algorithms.
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A. Fiat, R. M. Karp, M. Luby, L. A. McGeoch, D. D. Sleator, and N. E. Young. Competitive paging algorithms. Technical Report CMU-CS-88-196, Carnegie Mellon University, Pittsburgh, PA, 1988.
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Amos Fiat, Richard Karp, Mike Luby, Lyle McGeoch, Daniel Sleator, and Neal E. Young. Competitive paging algorithms. Journal of Algorithms, 12(4):685--699, December 1991.
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A. Fiat, R. Karp, M. Luby, L. McGeoch, D. Sleator, and N. Young. Competitive paging algorithms. Journal of Algorithms, 12:685--699, 1991.
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A. Fiat, R. Karp, M. Luby, L. McGeoch, D. Sleator, and N. Young. Competitive paging algorithms. Journal of Algorithms, 12:685-699, 1991.
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A. Fiat, R. M. Karp, M. Luby, L. A. McGeoch, D. D. Sleator, and N. E. Young. Competitive paging algorithms. Journal of Algorithms, 12:685--699, 1991.
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Amos Fiat, Richard Karp, M. Luby, L. A. McGeoch, Daniel D. Sleator, and N. E. Young. Competitive paging algorithms. Journal of Algorithms, 12:685--699, 1991.
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A. Fiat, R. Karp, M. Luby, L.A. McGeoch, D.Sleator, and N.E. Young. Competitive paging algorithms, Journal of Algorithms 12:685-699, 1991.
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Amos Fiat, Richard Karp, Mike Luby, Lyle McGeoch, Daniel Sleator, and Neal E. Young. Competitive paging algorithms. Journal of Algorithms, 12(4):685--699, December 1991.
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Amos Fiat, Richard Karp, Michael Luby, Lyle A. McGeoch, Daniel Sleator, and Neal E. Young. Competitive paging algorithms. Journal of Algorithms, 12:685-699, 1991.
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A. Fiat, R. M. Karp, M. Luby, L. A. McGeoch, D. D. Sleator and N. E. Young, "Competitive Paging Algorithms ", J. Algorithms, 1991, Vol. 12, No. 4, pp. 685-699.
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A. Fiat, R. Karp, M. Luby, L. McGeoch, D. Sleator, and N. Young. "Competitive paging algorithms," Journal of Algorithms, 12(1991), pp. 685-699.
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A. Fiat, R.M. Karp, M. Luby, L.A. McGeoch, D.D. Sleator and N.E. Young, "Competitive paging algorithms", Journal of Algorithms 12, pp. 685-699, 1991.
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A. Fiat, R. Karp, M. Luby, L. A. McGeoch, D. Sleator, and N.E. Young. Competitive paging algorithms. Journal of Algorithms, 12:685--699, 1991.
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