The problem of metrical service systems with multiple servers ((k,l)\documentclass[12pt]{minimal}
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\begin{document}$$(k,l)$$\end{document}-MSSMS), proposed by Feuerstein (LATIN’98: Theoretical Informatics, Third Latin American Symposium, 1998), is to service requests, each of which is an l\documentclass[12pt]{minimal}
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\begin{document}$$l$$\end{document}-point subset of a metric space, using k\documentclass[12pt]{minimal}
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\begin{document}$$k$$\end{document} servers in an online manner, minimizing the distance traveled by the servers. We prove that Feuerstein’s deterministic algorithm for (k,l)\documentclass[12pt]{minimal}
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\begin{document}$$(k,l)$$\end{document}-MSSMS actually achieves an improved competitive ratio of kk+ll-1\documentclass[12pt]{minimal}
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\begin{document}$$k\left( {{k+l}\atopwithdelims (){l}}-1\right) $$\end{document} on uniform metrics. In the randomized online setting on uniform metrics, we give an algorithm which achieves a competitive ratio O(k3logl)\documentclass[12pt]{minimal}
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\begin{document}$$\mathcal {O}(k^3\log l)$$\end{document}, beating the deterministic lower bound of k+ll-1\documentclass[12pt]{minimal}
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\begin{document}$${{k+l}\atopwithdelims (){l}}-1$$\end{document}. We prove that any randomized algorithm for (k,l)\documentclass[12pt]{minimal}
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\begin{document}$$(k,l)$$\end{document}-MSSMS on uniform metrics must be Ω(logkl)\documentclass[12pt]{minimal}
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\begin{document}$$\varOmega (\log kl)$$\end{document}-competitive. For the offline (k,l)\documentclass[12pt]{minimal}
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\begin{document}$$(k,l)$$\end{document}-MSSMS, we give a factor l\documentclass[12pt]{minimal}
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\begin{document}$$l$$\end{document} pseudo-approximation algorithm using kl\documentclass[12pt]{minimal}
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\begin{document}$$kl$$\end{document} servers on any metric space, and prove a matching hardness result, that a pseudo-approximation using less than kl\documentclass[12pt]{minimal}
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\begin{document}$$kl$$\end{document} servers is unlikely, even on uniform metrics.