On approximating arbitrary metrices by tree metrics
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
A comparative analysis of disk scheduling policies
Communications of the ACM
Journal of Algorithms
Online Scheduling for Sorting Buffers
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
Probabilistic approximation of metric spaces and its algorithmic applications
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
A tight bound on approximating arbitrary metrics by tree metrics
Journal of Computer and System Sciences - Special issue: STOC 2003
Improved online algorithms for the sorting buffer problem
STACS'07 Proceedings of the 24th annual conference on Theoretical aspects of computer science
Evaluation of online strategies for reordering buffers
WEA'06 Proceedings of the 5th international conference on Experimental Algorithms
Online sorting buffers on line
STACS'06 Proceedings of the 23rd Annual conference on Theoretical Aspects of Computer Science
Reordering buffer management for non-uniform cost models
ICALP'05 Proceedings of the 32nd international conference on Automata, Languages and Programming
Exploiting locality: approximating sorting buffers
WAOA'05 Proceedings of the Third international conference on Approximation and Online Algorithms
Offline sorting buffers on line
ISAAC'06 Proceedings of the 17th international conference on Algorithms and Computation
Evaluation of online strategies for reordering buffers
Journal of Experimental Algorithmics (JEA)
Buffer management for colored packets with deadlines
Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures
Improved online algorithms for the sorting buffer problem on line metrics
ACM Transactions on Algorithms (TALG)
Online and offline algorithms for the sorting buffers problem on the line metric
Journal of Discrete Algorithms
An improved competitive algorithm for reordering buffer management
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
APPROX/RANDOM'10 Proceedings of the 13th international conference on Approximation, and 14 the International conference on Randomization, and combinatorial optimization: algorithms and techniques
Almost tight bounds for reordering buffer management
Proceedings of the forty-third annual ACM symposium on Theory of computing
A note on sorting buffers offline
Theoretical Computer Science
Optimal online buffer scheduling for block devices
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
A bicriteria approximation for the reordering buffer problem
ESA'12 Proceedings of the 20th Annual European conference on Algorithms
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In the reordering buffer problem, we are given an input sequence of requests for service each of which corresponds to a point in a metric space. The cost of serving the requests heavily depends on the processing order. Serving a request induces cost corresponding to the distance between itself and the previously served request, measured in the underlying metric space. A reordering buffer with storage capacity k can be used to reorder the input sequence in a restricted fashion so as to construct an output sequence with lower service cost. This simple and universal framework is useful for many applications in computer science and economics, e.g., disk scheduling, rendering in computer graphics, or painting shops in car plants. In this paper, we design online algorithms for the reordering buffer problem. Our main result is a strategy with a polylogarithmic competitive ratio for general metric spaces. Previous work on the reordering buffer problem only considered very restricted metric spaces. We obtain our result by first developing a deterministic algorithm for arbitrary weighted trees with a competitive ratio of O(D · log k), where D denotes the unweighted diameter of the tree, i.e., the maximum number of edges on a path connecting two nodes. Then we show how to improve this competitive ratio to O(log2 k) for metric spaces that are derived from HSTs. Combining this result with the results on probabilistically approximating arbitrary metrics by tree metrics, we obtain a randomized strategy for general metric spaces that achieves a competitive ratio of O(log2 k · log n) in expectation against an oblivious adversary. Here n denotes the number of distinct points in the metric space. Note that the length of the input sequence can be much larger than n.