Amortized efficiency of list update and paging rules
Communications of the ACM
Competitive algorithms for server problems
Journal of Algorithms
An optimal on-line algorithm for K-servers on trees
SIAM Journal on Computing
New results on server problems
SIAM Journal on Discrete Mathematics
Journal of Algorithms
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Journal of the ACM (JACM)
Information Processing Letters
Online computation and competitive analysis
Online computation and competitive analysis
Competitive analysis of randomized paging algorithms
Theoretical Computer Science
On metric ramsey-type phenomena
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Weak Adversaries for the k-Server Problem
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
A Primal-Dual Randomized Algorithm for Weighted Paging
FOCS '07 Proceedings of the 48th Annual IEEE Symposium on Foundations of Computer Science
Randomized k-server on hierarchical binary trees
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Metrical task systems and the k-server problem on HSTs
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming
Computer Science Review
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We define a natural generalization of the prominent k-server problem, the k-resource problem. It occurs in a metric space with some integer demands given at its points. The demands may vary with time, but the total demand may never exceed k. An online algorithm has k servers at its disposal and its goal is to satisfy demands by moving servers, while minimizing the cost of their transport. We show asymptotically tight bounds on the competitive ratio of the k-resource problem in the uniform metric space of n points: we prove that the optimal competitive ratios are between min{k,n-1} and min{k,2(n-1)} for deterministic algorithms and between min{H"k,H"n"-"1} and min{H"k,2@?H"n"-"1} for randomized ones. This extends known results for k-server in such spaces to the more general setting of k-resource.