In the content-oblivious model, communication is limited to sending content-less pulses over asynchronous channels. Despite this extreme restriction, Censor-Hillel et al. (Dist. Comp., 2023) showed that any computation can be simulated on 2-edge-connected graphs, assuming a designated leader. Subsequent work investigated the necessity of this assumption. Frei et al. (DISC 2024, Dist. Comp. 2026) and Chalopin et al. (DISC 2025) designed content-oblivious leader-election algorithms for rings, thereby eliminating the need for an initial leader. Non-uniform leader election is possible on 2-edge-connected graphs (Chalopin et al., DISC 2025).

We obtain better algorithms for computing more balanced orientations and degree splits in Local. Important to our result is a connection to the hypergraph sinkless orientation problem [9, SODA'25]. We design an algorithm of complexity O(ϵ-1 · log n) for computing a balanced orientation with discrepancy at most ϵ · deg(v) for every vertex v ∈ V. This improves upon a previous result by [16, Distrib. Comput. 2020] of complexity O(ϵ-1 · log ϵ-1 · (log log ϵ-1)1.71 •log n). Further, we show that this result can also be extended to compute undirected degree splits with the same discrepancy and in the same runtime.

We give a simple deterministic algorithm for Sinkless Orientation in Congest achieving optimal complexity Θ(logδ n) on poly(n)-node graphs of minimum degree δ ≥ 3. Combined with the shattering argument by Ghaffari and Su [8, SODA 2017] for this problem, our result also implies an optimal randomized algorithm running in Θ(logδ log n) Congest rounds. Other known reductions imply corollaries for more balanced orientations, such as ones where nodes have at least ⌊deg/3⌋ incoming and outgoing edges. Our algorithm is arguably much simpler than the previous algorithm achieving optimal complexity in Local.

Recent improvements on the deterministic complexities of fundamental graph problems in the LOCAL model of distributed computing have yielded state-of-the-art upper bounds of \(\tilde{O}(\log^{5/3} n)\) rounds for maximal independent set (MIS) and \((\Delta + 1)\)-coloring [Ghaffari, Grunau, FOCS’24], and \(\tilde{O}(\log^{19/9} n)\) rounds for the more restrictive \(\Delta\)-coloring problem [Ghaffari, Kuhn, FOCS’21; Ghaffari, Grunau, FOCS’24; Bourreau, Brandt, Nolin, STOC’25]. In our work, we show that \(\Delta\)-coloring can be solved deterministically in \(\tilde{O}(\log^{5/3} n)\) rounds as well, matching the currently best bound for \((\Delta + 1)\)-coloring.

In a rendezvous task, a set of mobile agents initially dispersed in a network have to gather at an arbitrary common site. We consider the rendezvous problem on the infinite labeled line, with 2 initially asleep agents, without communication, and a synchronous notion of time. Each node on the line is labeled with a unique positive integer. The initial distance between the two agents is denoted by D. Time is divided into rounds and measured from the moment an agent first wakes up. We denote by τ the delay between the two agents' wake up times. If awake in a given round T, an agent at a node v has three options: stay at the node v, take port 0, or take port 1. If it decides to stay, the agent will still be at node v in round T+1. Otherwise, it will be at one of the two neighbors of v on the infinite line, depending on the port it chose. The agents achieve rendezvous in T rounds if they are at the same node in round T. We aim for a deterministic algorithm for this problem. The problem was recently considered by Miller and Pelc [Distributed Computing, 2025]. With 𝓁_{max} the largest label of the two starting nodes, they showed that no algorithm can guarantee rendezvous in o(D log^* 𝓁_{max}) rounds. The lower bound follows from a connection with the LOCAL model of distributed computing, and holds even if the agents are guaranteed simultaneous wake-up (τ = 0) and are told their initial distance D. Miller and Pelc also gave an algorithm of optimal matching complexity O(D log^* 𝓁_{max}) when the agents know D, but only obtained the higher bound of O(D² (log^* 𝓁_{max})³) when D is unknown to the agents. In this paper, we improve this second complexity to a tight O(D log^* 𝓁_{max}), closing the gap between the best known lower and upper bounds. In fact, our algorithm achieves rendezvous in O(D log^* 𝓁_{min}) rounds, where 𝓁_{min} is the smallest label within distance O(D) of the two starting positions. We obtain this result by having the agents compute sparse subsets of the nodes to gather at (formally, ruling sets over the line), as well as some general observations about the setting of rendezvous on labeled graphs.

In content-oblivious computation, n nodes wish to compute a given task over an asynchronous network that suffers from an extremely harsh type of noise, which corrupts the content of all messages across all channels. In a recent work, Censor-Hillel, Cohen, Gelles, and Sela (Distributed Computing, 2023) showed how to perform arbitrary computations in a content-oblivious way in 2-edge connected networks but only if the network has a distinguished node (called root) to initiate the computation. Our goal is to remove this assumption, which was conjectured to be necessary. Achieving this goal essentially reduces to performing a content-oblivious leader election since an elected leader can then serve as the root required to perform arbitrary content-oblivious computations. We focus on ring networks, which are the simplest 2-edge connected graphs. On oriented rings, we obtain a leader election algorithm with message complexity $$O(n \cdot \textsf{ID}_{\max })$$ , where $$\textsf{ID}_{\max }$$ is the maximal assigned ID. As it turns out, this dependency on $$\textsf{ID}_{\max }$$ is inherent: we show a lower bound of $$\Omega (n \log {\textsf{ID}_{\max }})$$ messages for content-oblivious leader election algorithms. We also extend our results to non-oriented rings. Here, however, the algorithm does not terminate but only quiescently stabilizes: all nodes eventually settle on an internal decision and stop receiving messages. Preliminary versions of parts of this research have appeared at the conferences PODC 2024 as a brief announcement and at DISC 2024 as a full paper.

In a rendezvous task, a set of mobile agents initially dispersed in a network have to gather at an arbitrary common site. We consider the rendezvous problem on the infinite labeled line, with 2 initially asleep agents, without communication, and a synchronous notion of time. Each node on the line is labeled with a unique positive integer. The initial distance between the two agents is denoted by D. Time is divided into rounds. We count time from the first moment that an agent wakes up, and denote by τ the delay in two agents' wake up times. If awake in a given round T, an agent at a node υ has three options: stay at the node υ, take port 0, or take port 1. If it decides to stay, the agent will still be at node υ in round T + 1. Otherwise, it will be at one of the two neighbors of υ on the infinite line, depending on the port it chose. The agents achieve rendezvous in T rounds if they are at the same node in round T. We aim for a deterministic algorithm for this problem.

Graph coloring is fundamental to distributed computing. We give the first sub-logarithmic distributed algorithm for coloring cluster graphs. These graphs are obtained from the underlying communication network by contracting nodes and edges, and they appear frequently as components in the study of distributed algorithms. In particular, we give a O (log* n)-round algorithm to (Δ + 1)-color cluster graphs of at least polylogarithmic degree. The previous best bound known was poly(log n) [Flin et al., SODA'24]. This properly generalizes results in the CONGEST model and shows that distributed graph problems can be solved quickly even when the node itself is decentralized.

Brooks’ theorem states that all connected graphs but odd cycles and cliques can be colored with Δ colors, where Δ is the maximum degree of the graph. Such colorings have been shown to admit non-trivial distributed algorithms [Panconesi and Srinivasan, Combinatorica 1995] and have been studied intensively in the distributed literature. In particular, it is known that any deterministic algorithm computing a Δ-coloring requires Ω(logn) rounds in the LOCAL model [Chang, Kopelowitz, and Pettie, FOCS 2016], and that this lower bound holds already on constant-degree graphs. In contrast, the best upper bound in this setting is given by an O(log2 n)-round deterministic algorithm that can be inferred already from the works of [Awerbuch, Goldberg, Luby, and Plotkin, FOCS 1989] and [Panconesi and Srinivasan, Combinatorica 1995] roughly three decades ago, raising the fundamental question about the true complexity of Δ-coloring in the constant-degree setting. We answer this long-standing question almost completely by providing an almost-optimal deterministic O(logn log* n)-round algorithm for Δ-coloring, matching the lower bound up to a log* n-factor. Similarly, in the randomized LOCAL model, we provide an O(loglogn log* n)-round algorithm, improving over the state-of-the-art upper bound of O(log2 logn) [Ghaffari, Hirvonen, Kuhn, and Maus, Distributed Computing 2021] and almost matching the Ω(loglogn)-round lower bound by [BFHKLRSU, STOC 2016]. Our results make progress on several important open problems and conjectures. One key ingredient for obtaining our results is the introduction of ruling subgraph families as a novel tool for breaking symmetry between substructures of a graph, which we expect to be of independent interest.

In content-oblivious computation, n nodes wish to compute a given task over an asynchronous network that suffers from an extremely harsh type of noise, which corrupts the content of all messages across all channels. In a recent work, Censor-Hillel, Cohen, Gelles, and Sela (Distributed Computing, 2023) showed how to perform arbitrary computations in a content-oblivious way in 2-edge connected networks but only if the network has a distinguished node (called root) to initiate the computation.

The celebrated palette sparsification result of [Assadi, Chen, and Khanna SODA’19] shows that to compute a Δ + 1 coloring of the graph, where Δ denotes the maximum degree, it suffices if each node limits its color choice to O(log n) independently sampled colors in {1, 2,…, Δ + 1}. They showed that it is possible to color the resulting sparsified graph—the spanning subgraph with edges between neighbors that sampled a common color, which are only Õ(n) edges—and obtain a Δ + 1 coloring for the original graph. However, to compute the actual coloring, that information must be gathered at a single location for centralized processing. We seek instead a local algorithm to compute such a coloring in the sparsified graph. The question is if this can be achieved in poly (log n) distributed rounds with small messages.

Graph coloring is fundamental to distributed computing. We give the first general treatment of the coloring of virtual graphs, where the graph $H$ to be colored is locally embedded within the communication graph $G$. Besides generalizing classical distributed graph coloring (where $H=G$), this captures other previously studied settings, including cluster graphs and power graphs. We find that the complexity of coloring a virtual graph depends on the edge congestion of its embedding. The main question of interest is how fast we can color virtual graphs of constant congestion. We find that, surprisingly, these graphs can be colored nearly as fast as ordinary graphs. Namely, we give a $O(\log^4\log n)$-round algorithm for the deg+1-coloring problem, where each node is assigned more colors than its degree. This can be viewed as a case where a distributed graph problem can be solved even when the operation of each node is decentralized.

In content-oblivious computation, n nodes wish to compute a given task over an asynchronous network that suffers from an extremely harsh type of noise, which corrupts the content of all messages across all channels. In a recent work, Censor-Hillel, Cohen, Gelles, and Sela (Distributed Computing, 2023) showed how to perform arbitrary computations in a content-oblivious way in 2-edge connected networks but only if the network has a distinguished node (called root) to initiate the computation. Our goal is to remove this assumption, which was conjectured to be necessary. Achieving this goal essentially reduces to performing a content-oblivious leader election since an elected leader can then serve as the root required to perform arbitrary content-oblivious computations. We focus on ring networks, which are the simplest 2-edge connected graphs. On oriented rings, we obtain a leader election algorithm with message complexity O(n*ID_max), where ID_max is the maximal assigned ID. As it turns out, this dependency on $ID_max$ is inherent: we show a lower bound of Omega(n*log(ID_max/n)) messages for content-oblivious leader election algorithms. We also extend our results to non-oriented rings, where nodes cannot tell which channel leads to which neighbor. In this case, however, the algorithm does not terminate but only reaches quiescence.

We present an O(log3 log n)-round distributed algorithm for the (Δ + 1)-coloring problem, where each node broadcasts only one O(log n)-bit message per round to its neighbors. Previously, the best such broadcast-based algorithm required O(log n) rounds. If Δ ∈ Ω(log 3 n), our algorithm runs in O(log* n) rounds. Our algorithm's round complexity matches the state-of-the-art in the much more powerful CONGEST model [Halldórsson et al., STOC'21 & PODC'22], where each node sends one different message to each of its neighbors, thus sending up to Θ(n log n) bits per round. This is the best complexity known, even if message sizes are unbounded.

We provide a $O(\log^6 \log n)$-round randomized algorithm for distance-2 coloring in CONGEST with $Δ^2+1$ colors. For $Δ\gg\operatorname{poly}\log n$, this improves exponentially on the $O(\logΔ+\operatorname{poly}\log\log n)$ algorithm of [Halldórsson, Kuhn, Maus, Nolin, DISC'20]. Our study is motivated by the ubiquity and hardness of local reductions in CONGEST. For instance, algorithms for the Local Lovász Lemma [Moser, Tardos, JACM'10; Fischer, Ghaffari, DISC'17; Davies, SODA'23] usually assume communication on the conflict graph, which can be simulated in LOCAL with only constant overhead, while this may be prohibitively expensive in CONGEST. We hope our techniques help tackle in CONGEST other coloring problems defined by local relations.

We present a new technique to efficiently sample and communicate a large number of elements from a distributed sampling space. When used in the context of a recent Local algorithm for (degree +1)-list-coloring (D1LC), this allows us to solve D1LC in O(log5 logn) Congest rounds, and in only O(log* n) rounds when the graph has minimum degree Ω(log7 n), w.h.p.

We present a new approach to randomized distributed graph coloring that is simpler and more efficient than previous ones. In particular, it allows us to tackle the (deg+1)-list-coloring (D1LC) problem, where each node v of degree dv is assigned a palette of dv+1 colors, and the objective is to find a proper coloring using these palettes. While for (Δ+1)-coloring (where Δ is the maximum degree), there is a fast randomized distributed O(log3logn)-round algorithm due to Chang, Li, and Pettie, no o(logn)-round algorithms are known for the D1LC problem.

We present ${\rm poly\log\log n}$-round randomized distributed algorithms to compute vertex splittings, a partition of the vertices of a graph into $k$ parts such that a node of degree $d(u)$ has $\approx d(u)/k$ neighbors in each part. Our techniques can be seen as the first progress towards general ${\rm poly\log\log n}$-round algorithms for the Lovász Local Lemma. As the main application of our result, we obtain a randomized ${\rm poly\log\log n}$-round CONGEST algorithm for $(1+ε)Δ$-edge coloring $n$-node graphs of sufficiently large constant maximum degree $Δ$, for any $ε>0$. Further, our results improve the computation of defective colorings and certain tight list coloring problems. All the results improve the state-of-the-art round complexity exponentially, even in the LOCAL model.

We give an improved randomized CONGEST algorithm for distance-$2$ coloring that uses $Δ^2+1$ colors and runs in $O(\log n)$ rounds, improving the recent $O(\log Δ\cdot \log n)$-round algorithm in [Halldórsson, Kuhn, Maus; PODC '20]. We then improve the time complexity to $O(\log Δ) + 2^{O(\sqrt{\log\log n})}$.