Memory versus randomization in on-line algorithms
IBM Journal of Research and Development
Finding Worst-Case Instances of, and Lower Bounds for, Online Algorithms Using Genetic Algorithms
AI '02 Proceedings of the 15th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
A New Competitive Analysis of Randomized Caching
ISAAC '00 Proceedings of the 11th International Conference on Algorithms and Computation
The CNN Problem and Other k-Server Variants
STACS '00 Proceedings of the 17th Annual Symposium on Theoretical Aspects of Computer Science
A Decentralized Algorithm for Coordinating Independent Peers: An Initial Examination
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
On Multicriteria Online Problems
ESA '00 Proceedings of the 8th Annual European Symposium on Algorithms
Randomized k-server on hierarchical binary trees
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
A Risk-Reward Competitive Analysis for the Recoverable Canadian Traveller Problem
COCOA 2008 Proceedings of the 2nd international conference on Combinatorial Optimization and Applications
On the bicriteria k-server problem
ACM Transactions on Algorithms (TALG)
Computer Science Review
The communication complexity of distributed task allocation
PODC '12 Proceedings of the 2012 ACM symposium on Principles of distributed computing
| Hi-index | 0.00 |
Deterministic competitive k-server algorithms are given for all k and all metric spaces. This settles the k-server conjecture of M.S. Manasse et al. (1988) up to the competitive ratio. The best previous result for general metric spaces was a three-server randomized competitive algorithm and a nonconstructive proof that a deterministic three-server competitive algorithm exists. The competitive ratio the present authors can prove is exponential in the number of servers. Thus, the question of the minimal competitive ratio for arbitrary metric spaces is still open. The methods set forth here also give competitive algorithms for a natural generalization of the k-server problem, called the k-taxicab problem.