Abstract
In the k-server problem we wish to minimize, in an online fashion, the movement cost of k servers in response to a sequence of requests. For two servers, it is known that the optimal deterministic algorithm has competitive ratio 2, and it has been a long-standing open problem whether it is possible to improve this ratio using randomization. We give a positive answer to this problem when the underlying metric space is a real line, by providing a randomized online algorithm for this case with competitive ratio at most 155/78 ≈ 1.987. This is the first algorithm for two servers that achieves a competitive ratio smaller than 2 in a nonuniform metric space with more than three points. We consider a more general problem called the (k, l)-server problem, in which a request is served using l out of k available servers. We show that the randomized 2-server problem can be reduced to the deterministic (2l,l)-server problem. We prove a lower bound of 2 on the competitive ratio of the (4, 2)-server problem. This implies that one unbiased random bit is not sufficient to improve the ratio of 2 for the two-server problem. Then we give a 155/78-competitive algorithm for the (6, 3)-server problem on the real line. Our algorithm is simple and memoryless. The solution has been obtained using linear programming techniques that may have applications for other online problems.
| Original language | English |
|---|---|
| Pages (from-to) | 53-69 |
| Number of pages | 17 |
| Journal | Information and Computation |
| Volume | 158 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2000 |
| Externally published | Yes |
Bibliographical note
Funding Information:1This research was partially conducted while the author was at International Computer Science Institute, University of California, Berkeley. 2Research supported by NSF Grant CCR-9503498. This research was partially conducted when the author was visiting International Computer Science Institute, University of California, Berkeley. 3Research supported by NSF Grant CCR-9503441.
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