Competitive algorithms for server problems
Journal of Algorithms
New results on server problems
SIAM Journal on Discrete Mathematics
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Approximation algorithms for NP-hard problems
Online computation and competitive analysis
Online computation and competitive analysis
Theoretical Improvements in Algorithmic Efficiency for Network Flow Problems
Journal of the ACM (JACM)
Weak Adversaries for the k-Server Problem
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
On the competitive ratio of the work function algorithm for the k-server problem
Theoretical Computer Science - Special issue: Online algorithms in memoriam, Steve Seiden
Linear Programming and Network Flows
Linear Programming and Network Flows
On the bicriteria k-server problem
ACM Transactions on Algorithms (TALG)
On the additive constant of the k-server Work Function Algorithm
Information Processing Letters
Online computation with advice
Theoretical Computer Science
On the advice complexity of the k-server problem
ICALP'11 Proceedings of the 38th international colloquim conference on Automata, languages and programming - Volume Part I
A Polylogarithmic-Competitive Algorithm for the k-Server Problem
FOCS '11 Proceedings of the 2011 IEEE 52nd Annual Symposium on Foundations of Computer Science
Computer Science Review
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This paper is concerned with two algorithms for solving the k-server problem: the optimal off-line algorithm (OPT) and the on-line work function algorithm (WFA). Both algorithms are usually implemented by network flow techniques including the flow augmentation method. In the paper a new implementation approach is proposed, which is again based on network flows, but uses simpler networks and the cost reduction method. The paper describes in detail the corresponding new implementations of OPT and WFA, respectively. All necessary correctness proofs are given. Also, experiments are presented, which confirm that the new approach assures faster execution of both algorithms.