We consider online algorithms for the k-server problem on trees. Chrobak and Larmore proposed a k-competitive algorithm for this problem that has the optimal competitive ratio. However, a naive implementation of their algorithm has O(n) time complexity for processing each query, where n is the number of nodes in the tree. We propose a new time-efficient implementation of this algorithm that has O(n\log n) time complexity for preprocessing and O\left(k^2 + k\cdot \log n\right) time for processing a query. We also propose a quantum algorithm for the case where the nodes of the tree are presented using string paths. In this case, no preprocessing is needed, and the time complexity for each query is O(k^2n\log n). When the number of queries is o\left(\sqrt{n}{k^2\log n}\right), we obtain a quantum speed-up on the total runtime compared to our classical algorithm. Our algorithm builds on a result of independent interest: we give a quantum algorithm to find the first marked element in a collection of m objects, that works even in the presence of two-sided bounded errors on the input oracle. It has worst-case complexity O(m). In the particular case of one-sided errors on the input, it has expected time complexity O(x) where x is the position of the first marked element  .
We consider online algorithms for the k-server problem on trees. Chrobak and Larmore proposed a k-competitive algorithm for this problem that has the optimal competitive ratio. However, a naive implementation of their algorithm has O(n) time complexity for processing each query, where n is the number of nodes in the tree. We propose a new time-efficient implementation of this algorithm that has O(n\log n) time complexity for preprocessing and O\left(k^2 + k\cdot \log n\right) time for processing a query. We also propose a quantum algorithm for the case where the nodes of the tree are presented using string paths. In this case, no preprocessing is needed, and the time complexity for each query is O(k^2n\log n). When the number of queries is o\left(\sqrt{n}{k^2\log n}\right), we obtain a quantum speed-up on the total runtime compared to our classical algorithm. We also give a simple quantum algorithm to find the first marked element in a collection of m objects, that works even in the presence of two-sided bounded errors on the input oracle. It has worst-case complexity O(m). In the particular case of one-sided errors on the input, it has expected time complexity O(x) where x is the position of the first marked element . Compare with previous work, our algorithm can handle errors in the input oracle .
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Our algorithm builds on a result of independent interest: we give a
We also give a simple
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. Compare with previous work, our algorithm can handle errors in the input oracle