Improved Worst-Case Deterministic Parallel Dynamic Minimum Spanning Forest
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This paper gives a new deterministic algorithm for the dynamic Minimum Spanning Forest (MSF) problem in the EREW PRAM model, where the goal is to maintain a MSF of a weighted graph with n vertices and m edges while supporting edge insertions and deletions. We show that one can solve the dynamic MSF problem using O(√(n)) processors and O( n) worst-case update time, for a total of O(√(n) n) work. This improves on the work of Ferragina [IPPS 1995] which costs O( n) worst-case update time and O(n^2/3m/n) work.
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