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1. Streaming Algorithms for Network Design

   https://doi.org/10.4230/lipics.approx/random.2025.4  

   Chekuri, Chandra; Jain, Rhea; Mahabadi, Sepideh; Vakilian, Ali (January 2025, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Ene, Alina; Chattopadhyay, Eshan (Ed.)

   We consider the Survivable Network Design problem (SNDP) in the single-pass insertion-only streaming model. The input to SNDP is an edge-weighted graph G = (V, E) and an integer connectivity requirement r(uv) for each u, v ∈ V. The objective is to find a minimum-weight subgraph H ⊆ G such that, for every pair of vertices u, v ∈ V, u and v are r(uv)-edge/vertex-connected. Recent work by [Ce Jin et al., 2024] obtained approximation algorithms for edge-connectivity augmentation, and via that, also derived algorithms for edge-connectivity SNDP (EC-SNDP). In this work we consider vertex-connectivity setting (VC-SNDP) and obtain several results for it as well as improved results for EC-SNDP. - We provide a general framework for solving connectivity problems including SNDP and others in streaming; this is based on a connection to fault-tolerant spanners. For VC-SNDP we provide an O(tk)-approximation in Õ(k^{1-1/t}n^{1 + 1/t}) space, where k is the maximum connectivity requirement, assuming an exact algorithm at the end of the stream. Using a refined LP-based analysis, we provide an O(β t)-approximation where β is the integrality gap of the natural cut-based LP relaxation. These are the first approximation algorithms in the streaming model for VC-SNDP. When applied to the EC-SNDP, our framework provides an O(t)-approximation in Õ(k^{1/2-1/(2t)}n^{1 + 1/t} + kn) space, improving the O(t log k)-approximation of [Ce Jin et al., 2024] using Õ(kn^{1+1/t}) space; this also extends to element-connectivity SNDP. - We consider vertex connectivity-augmentation in the link-arrival model. The input is a k-vertex-connected spanning subgraph G, and additional weighted links L arrive in the stream; the goal is to store the min-weight set of links such that G ∪ L is (k+1)-vertex-connected. We obtain constant-factor approximations in near-linear space for k = 1, 2. Our result for k = 2 is based on using the SPQR tree, a novel application for this well-known representation of 2-connected graphs. 

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2. Parallel Reachability and Shortest Paths on Non-Sparse Digraphs: Near-Linear Work and Sub-Square-Root Depth

   https://doi.org/10.4230/lipics.icalp.2026.15  

   Ashvinkumar, Vikrant; Bernstein, Aaron; Gutenberg, Maximilian Probst; Saranurak, Thatchaphol (January 2026, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Bhattacharya, Sayan; Nanongkai, Danupon; Benedikt, Michael; Puppis, Gabriele (Ed.)

   Abstract: We present parallel algorithms for computing single-source reachability and shortest paths on directed n-vertex m-edge graphs using near-linear Õ(m) work and o(√n) depth whenever m ≥ n^{1+o(1)}. At the extreme of m = Ω(n²), our reachability and shortest path algorithms have depth only n^0.136 and n^{0.25+o(1)}, respectively. The state-of-the-art parallel algorithms with near-linear work for both problems [Jambulapati et al., 2019; Cao et al., 2020; Rozhoň et al., 2023; Cao and Fineman, 2023; Brand et al., 2025] require Ω(√n) depth in all density regimes. 

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3. A Simple Deterministic Near-Linear Time Approximation Scheme for Transshipment with Arbitrary Positive Edge Costs

   https://doi.org/10.4230/LIPIcs.ESA.2024.56  

   Fox, Emily (January 2024, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Chan, Timothy; Fischer, Johannes; Iacono, John; Herman, Grzegorz (Ed.)

   We describe a simple deterministic near-linear time approximation scheme for uncapacitated minimum cost flow in undirected graphs with positive real edge weights, a problem also known as transshipment. Specifically, our algorithm takes as input a (connected) undirected graph G = (V, E), vertex demands b ∈ R^V such that ∑_{v ∈ V} b(v) = 0, positive edge costs c ∈ R_{≥ 0}^E, and a parameter ε > 0. In O(ε^{-2} m log^{O(1)} n) time, it returns a flow f such that the net flow out of each vertex is equal to the vertex’s demand and the cost of the flow is within a (1 ± ε) factor of optimal. Our algorithm is combinatorial and has no running time dependency on the demands or edge costs. With the exception of a recent result presented at STOC 2022 for polynomially bounded edge weights, all almost- and near-linear time approximation schemes for transshipment relied on randomization to embed the problem instance into low-dimensional space. Our algorithm instead deterministically approximates the cost of routing decisions that would be made if the input were subject to a random tree embedding. To avoid computing the Ω(n²) vertex-vertex distances that an approximation of this kind suggests, we also take advantage of the clustering method used in the well-known Thorup-Zwick distance oracle. 

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4. Connectivity Oracle Under Vertex Failures by Shortcutting Unbreakable Decomposition

   https://doi.org/10.4230/lipics.icalp.2026.139  

   Li, Xizhe; Long, Yaowei; Pidugu, David; Saranurak, Thatchaphol; Wang, Benyu (January 2026, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Bhattacharya, Sayan; Nanongkai, Danupon; Benedikt, Michael; Puppis, Gabriele (Ed.)

   Abstract: We study connectivity oracle under vertex failures, one of the most fundamental graph data structures with many applications. We provide a new deterministic connectivity oracle that handles update in O(k⁶) time and answers query in O(k) time, while using 2^O(k²) n + O(k²n α_c(n)) space and k^O(k²) n + O(m + k³ n log² n + k⁶n log n) preprocessing time. Although some previous works achieve k² ⋅ n^o(1) update time and O(k) query time [Long and Saranurak, 2022; Yaowei Long and Yunfan Wang, 2024], the update time is still n-dependent, while oracles that have n-independent update and query times [Michal Pilipczuk et al., 2022; Jan van den Brand and Thatchaphol Saranurak, 2019] cannot achieve optimal O(k) query time [Monika Henzinger et al., 2015] and often have Ω(n²) space and processing time. Our solution would be the first vertex-failure connectivity oracle that achieves O(k) query time with update time completely independent of n, while improving space usage and having competitive preprocessing time. 

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5. Finding Most-Shattering Minimum Vertex Cuts of Polylogarithmic Size in Near-Linear Time

   https://doi.org/10.4230/LIPIcs.ICALP.2024.87  

   Hua, Kevin; Li, Daniel; Park, Jaewoo; Saranurak, Thatchaphol (January 2024, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Bringmann, Karl; Grohe, Martin; Puppis, Gabriele; Svensson, Ola (Ed.)

   We show the first near-linear time randomized algorithms for listing all minimum vertex cuts of polylogarithmic size that separate the graph into at least three connected components (also known as shredders) and for finding the most shattering one, i.e., the one maximizing the number of connected components. Our algorithms break the quadratic time bound by Cheriyan and Thurimella (STOC'96) for both problems that has been unimproved for more than two decades. Our work also removes an important bottleneck to near-linear time algorithms for the vertex connectivity augmentation problem (Jordan '95) and finding an even-length directed cycle in a graph, a problem shown to be equivalent to many other fundamental problems (Vazirani and Yannakakis '90, Robertson et al. '99). Note that it is necessary to list only minimum vertex cuts that separate the graph into at least three components because there can be an exponential number of minimum vertex cuts in general. To obtain a near-linear time algorithm, we have extended techniques in local flow algorithms developed by Forster et al. (SODA'20) to list shredders on a local scale. We also exploit fast queries to a pairwise vertex connectivity oracle subject to vertex failures (Long and Saranurak FOCS'22, Kosinas ESA'23). This is the first application of using connectivity oracles subject to vertex failures to speed up a static graph algorithm. 

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