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Geometric Bipartite Matching Based Exact Algorithms for Server Problems

Authors Sharath Raghvendra , Pouyan Shirzadian , Rachita Sowle

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ACM Subject Classification
  • Theory of computation → Computational geometry
Keywords
  • Minimum-Cost Bipartite Matching
  • Server Problems
  • Primal-Dual Approach

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Abstract

For any given metric space, obtaining an offline optimal solution to the classical k-server problem can be reduced to solving a minimum-cost partial bipartite matching between two point sets A and B within that metric space. 
For d-dimensional 𝓁_p metric space, we present an Õ(min{nk, n^{2-1/(2d+1)}log Δ}⋅ Φ(n)) time algorithm for solving this instance of minimum-cost partial bipartite matching; here, Δ represents the spread of the point set, and Φ(n) is the query/update time of a d-dimensional dynamic weighted nearest neighbor data structure. Our algorithm improves upon prior algorithms that require at least Ω(nkΦ(n)) time. The design of minimum-cost (partial) bipartite matching algorithms that make sub-quadratic queries to a weighted nearest-neighbor data structure, even for bounded spread instances, is a major open problem in computational geometry. We resolve this problem at least for the instances that are generated by the offline version of the k-server problem. 
Our algorithm employs a hierarchical partitioning approach, dividing the points of A∪ B into rectangles. It maintains a partial minimum-cost matching where any point b ∈ B is either matched to another point a ∈ A or to the boundary of the rectangle it is located in. The algorithm involves iteratively merging pairs of rectangles by erasing the shared boundary between them and recomputing the minimum-cost partial matching. This continues until all boundaries are erased and we obtain the desired minimum-cost partial matching of A and B. We exploit geometry in our analysis to show that each point participates in only Õ(n^{1-1/(2d+1)}log Δ) number of augmenting paths, leading to a total execution time of Õ(n^{2-1/(2d+1)}Φ(n)log Δ).
We also show that, for the 𝓁₁ norm and d dimensions, any algorithm that can solve instances of the offline n-server problem with an exponential spread in T(n) time can be used to compute minimum-cost bipartite matching in a complete graph defined on two (d-1)-dimensional point sets under the 𝓁₁ norm within T(n) time. This suggests that removing spread from the execution time of our algorithm may be difficult as it immediately results in a sub-quadratic algorithm for bipartite matching under the 𝓁₁ norm.

Cite As Get BibTex

Sharath Raghvendra, Pouyan Shirzadian, and Rachita Sowle. Geometric Bipartite Matching Based Exact Algorithms for Server Problems. In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 72:1-72:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.SoCG.2025.72

Author Details

Sharath Raghvendra
  • North Carolina State University, Raleigh, NC, USA
Pouyan Shirzadian
  • Virginia Tech, Blacksburg, VA, USA
Rachita Sowle
  • Virginia Commonwealth University, Richmond, VA, USA

Funding

This research was supported by NSF grants CCF 2514753 and CCF 2223871.

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