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تسجيل مستخدم جديدImproved 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 $O(sqrt n)$ processors and $O(log n)$ worst-case update time, for a total of $O(sqrt n log n)$ work. This improves on the work of Ferragina [IPPS 1995] which costs $O(log n)$ worst-case update time and $O(n^{2/3} log{frac{m}{n}})$ work.
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We give two fully dynamic algorithms that maintain a $(1+varepsilon)$-approximation of the weight $M$ of the minimum spanning forest of an $n$-node graph $G$ with edges weights in $[1,W]$, for any $varepsilon>0$. (1) Our deterministic algorithm tak
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