arXiv subjects

David Peleg

Publications and source records attributed to David Peleg.

At least 19 recordsLinked to original sources

arXiv2026

Distributed Algorithms for Near-Equitable Coloring

For an $n$-vertex graph of maximum degree $\Delta$ and diameter $D$, an equitable $(\Delta+1)$-coloring is a vertex coloring where the frequency of each color (namely, the number of vertices it colors) are all equal to $\sigma=n/(\Delta+1)$ (up to rounding). The Hajnal-Szemer\'edi Theorem guarantees the existence of such a coloring for every graph, and an $O(n^2\Delta)$ time sequential algorithm is known for computing such a coloring. Here, we study near-equitable graph coloring in distributed networks. The main question of interest is how close one can remain to the desired palette size of $\Delta+1$ while computing, in few distributed rounds, a coloring whose frequencies are close to $\sigma$. It appears that these two conflicting parameters exhibit a tradeoff, which we attempt to explore. We present a suite of fast randomized distributed algorithms representing varying points on this tradeoff, analyze their properties, and study their time complexity in the sequential, CONGEST and Congested Clique (CC) models.

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arXiv2026

Diameter-Free Distributed Frequency Control for Graph Coloring in the CONGEST Model

This paper presents two randomized proper-coloring algorithms that control color frequencies in the synchronous CONGEST model without paying a diameter-dependent coordination cost. Let $\lambda \geq 1$ denote the desired failure exponent. For every fixed $\delta > 0$, the first algorithm uses $\chi = \lceil (2+\delta)\Delta \rceil$ colors and, with probability at least $1 - n^{-\lambda}$, outputs a proper coloring that bounds the deviation of every color frequency from $n/\chi$ by $O_\delta(\sqrt{(\lambda+1)(n/\chi)\lg n} + (\lambda+1)\lg n)$. Under an explicit load condition, this additive guarantee yields two-sided relative balance. The second algorithm works with every $\chi > \Delta$ and gives a one-sided frequency cap controlled by the palette slack $\chi - \Delta$. In particular, it uses $\Delta + \lceil (\Delta+1)/\lceil \ln n \rceil \rceil$ colors and caps every used color class by $O((\lambda+1)(\sigma \lg^2 n + \lg n))$, where $\sigma = n/(\Delta+1)$. Both algorithms run in $O((\lambda+1)\lg n)$ rounds, with no dependence on the network diameter; for the first algorithm, the multiplicative constant in the time bound depends on $\delta$.

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arXiv2026

Recursive Energy Efficient Agreement

Agreement is a foundational problem in distributed computing that have been studied extensively for over four decades. Recently, Meir, Mirault, Peleg and Robinson introduced the notion of \emph{Energy Efficient Agreement}, where the goal is to solve Agreement while minimizing the number of round a party participates in, thereby reducing the energy cost per participant. We show a recursive Agreement algorithm that has $O(\log f)$ active rounds per participant, where $f<n$ represents the maximum number of crash faults in the system.

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arXiv2025

Optimized Degree Realization: Minimum Dominating Set & Maximum Matching

The Degree Realization problem requires, given a sequence $d$ of $n$ positive integers, to decide whether there exists a graph whose degrees correspond to $d$, and to construct such a graph if it exists. A more challenging variant of the problem arises when $d$ has many different realizations, and some of them may be more desirable than others. We study \emph{optimized realization} problems in which the goal is to compute a realization that optimizes some quality measure. Efficient algorithms are known for the problems of finding a realization with the maximum clique, the maximum independent set, or the minimum vertex cover. In this paper, we focus on two problems for which such algorithms were not known. The first is the Degree Realization with Minimum Dominating Set problem, where the goal is to find a realization whose minimum dominating set is minimized among all the realizations of the given sequence $d$. The second is the Degree Realization with Maximum Matching problem, where the goal is to find a realization with the largest matching among all the realizations of $d$. We present polynomial time realization algorithms for these two open problems. A related problem of interest and importance is \emph{characterizing} the sequences with a given value of the optimized function. This leads to an efficient computation of the optimized value without providing the realization that achieves that value. For the Maximum Matching problem, a succinct characterization of degree sequences with a maximum matching of a given size was known. This paper provides a succinct characterization of sequences with minimum dominating set of a given size.

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arXiv2025

Degree Realization by Bipartite Cactus Graphs

The \textsc{Degree Realization} problem with respect to a graph family $\mathcal{F}$ is defined as follows. The input is a sequence $d$ of $n$ positive integers, and the goal is to decide whether there exists a graph $G \in \mathcal{F}$ whose degrees correspond to $d$. The main challenges are to provide a precise characterization of all the sequences that admit a realization in $\mathcal{F}$ and to design efficient algorithms that construct one of the possible realizations, if one exists. This paper studies the problem of realizing degree sequences by bipartite cactus graphs (where the input is given as a single sequence, without the bi-partition). A characterization of the sequences that have a cactus realization is already known [28]. In this paper, we provide a systematic way to obtain such a characterization, accompanied by a realization algorithm. This allows us to derive a characterization for bipartite cactus graphs, and as a byproduct, also for several other interesting sub-families of cactus graphs, including bridge-less cactus graphs and core cactus graphs, as well as for the bipartite sub-families of these families.

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arXiv2025

Distributed Download from an External Data Source in Asynchronous Faulty Settings

The distributedData Retrieval (DR) model consists of $k$ peers connected by a complete peer-to-peer communication network, and a trusted external data source that stores an array $\textbf{X}$ of $n$ bits ($n \gg k$). Up to $\beta k$ of the peers might fail in any execution (for $\beta \in [0, 1)$). Peers can obtain the information either by inexpensive messages passed among themselves or through expensive queries to the source array $\textbf{X}$. In the DR model, we focus on designing protocols that minimize the number of queries performed by any nonfaulty peer (a measure referred to as query complexity) while maximizing the resilience parameter $\beta$. The Download problem requires each nonfaulty peer to correctly learn the entire array $\textbf{X}$. Earlier work on this problem focused on synchronous communication networks and established several deterministic and randomized upper and lower bounds. Our work is the first to extend the study of distributed data retrieval to asynchronous communication networks. We address the Download problem under both the Byzantine and crash failure models. We present query-optimal deterministic solutions in an asynchronous model that can tolerate any fixed fraction $\beta<1$ of crash faults. In the Byzantine failure model, it is known that deterministic protocols incur a query complexity of $\Omega(n)$ per peer, even under synchrony. We extend this lower bound to randomized protocols in the asynchronous model for $\beta \geq 1/2$, and further show that for $\beta < 1/2$, a randomized protocol exists with near-optimal query complexity. To the best of our knowledge, this is the first work to address the Download problem in asynchronous communication networks.

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arXiv2025

Time-Optimal and Energy-Efficient Deterministic Consensus

We study fault-tolerant consensus in a variant of the synchronous message passing model, where, in each round, every node can choose to be awake or asleep. This is known as the sleeping model (Chatterjee, Gmyr, Pandurangan PODC 2020) and defines the awake complexity (also called \emph{energy complexity}), which measures the maximum number of rounds that any node is awake throughout the execution. Only awake nodes can send and receive messages in a given round and all messages sent to sleeping nodes are lost. We present new deterministic consensus algorithms that tolerate up to $f<n$ crash failures, where $n$ is the number of nodes. Our algorithms match the optimal time complexity lower bound of $f+1$ rounds. For multi-value consensus, where the input values are chosen from some possibly large set, we achieve an energy complexity of ${O}(\lceil f^2 / n \rceil)$ rounds, whereas for binary consensus, we show that ${O}(\lceil f / \sqrt{n} \rceil)$ rounds are possible.

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arXiv2025

Degree Realization by Bipartite Multigraphs

The problem of realizing a given degree sequence by a multigraph can be thought of as a relaxation of the classical degree realization problem (where the realizing graph is simple). This paper concerns the case where the realizing multigraph is required to be bipartite. The problem of characterizing sequences that can be realized by a bipartite graph has two variants. In the simpler one, termed BDR$^P$, the partition of the sequence into two sides is given as part of the input. A complete characterization for realizability in this variant was given by Gale and Ryser over sixty years ago. However, the variant where the partition is not given, termed BDR, is still open. For bipartite multigraph realizations, there are also two variants. For BDR$^P$, where the partition is given as part of the input, a characterization was known for determining whether there is a multigraph realization whose underlying graph is bipartite, such that the maximum number of copies of an edge is at most $r$. We present a characterization for determining if there is a bipartite multigraph realization such that the total number of excess edges is at most $t$. We show that optimizing these two measures may lead to different realizations, and that optimizing by one measure may increase the other substantially. As for the variant BDR, where the partition is not given, we show that determining whether a given (single) sequence admits a bipartite multigraph realization is NP-hard. Moreover, we show that this hardness result extends to any graph family which is a sub-family of bipartite graphs and a super-family of paths. On the positive side, we provide an algorithm that computes optimal realizations for the case where the number of balanced partitions is polynomial, and present sufficient conditions for the existence of bipartite multigraph realizations that depend only on the largest degree of the sequence.

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arXiv2024

Distributed Download from an External Data Source in Faulty Majority Settings

We extend the study of retrieval problems in distributed networks, focusing on improving the efficiency and resilience of protocols in the \emph{Data Retrieval (DR) Model}. The DR Model consists of a complete network (i.e., a clique) with $k$ peers, up to $\beta k$ of which may be Byzantine (for $\beta \in [0, 1)$), and a trusted \emph{External Data Source} comprising an array $X$ of $n$ bits ($n \gg k$) that the peers can query. Additionally, the peers can also send messages to each other. In this work, we focus on the Download problem that requires all peers to learn $X$. Our primary goal is to minimize the maximum number of queries made by any honest peer and additionally optimize time. We begin with a randomized algorithm for the Download problem that achieves optimal query complexity up to a logarithmic factor. For the stronger dynamic adversary that can change the set of Byzantine peers from one round to the next, we achieve the optimal time complexity in peer-to-peer communication but with larger messages. In broadcast communication where all peers (including Byzantine peers) are required to send the same message to all peers, with larger messages, we achieve almost optimal time and query complexities for a dynamic adversary. Finally, in a more relaxed crash fault model, where peers stop responding after crashing, we address the Download problem in both synchronous and asynchronous settings. Using a deterministic protocol, we obtain nearly optimal results for both query complexity and message sizes in these scenarios.

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arXiv2024

Approximate Realizations for Outerplanaric Degree Sequences

We study the question of whether a sequence d = (d_1,d_2, \ldots, d_n) of positive integers is the degree sequence of some outerplanar (a.k.a. 1-page book embeddable) graph G. If so, G is an outerplanar realization of d and d is an outerplanaric sequence. The case where \sum d \leq 2n - 2 is easy, as d has a realization by a forest (which is trivially an outerplanar graph). In this paper, we consider the family \cD of all sequences d of even sum 2n\leq \sum d \le 4n-6-2\multipl_1, where \multipl_x is the number of x's in d. (The second inequality is a necessary condition for a sequence d with \sum d\geq 2n to be outerplanaric.) We partition \cD into two disjoint subfamilies, \cD=\cD_{NOP}\cup\cD_{2PBE}, such that every sequence in \cD_{NOP} is provably non-outerplanaric, and every sequence in \cD_{2PBE} is given a realizing graph $G$ enjoying a 2-page book embedding (and moreover, one of the pages is also bipartite).

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arXiv2023

Byzantine Resilient Computing with the Cloud

We study a framework for modeling distributed network systems assisted by a reliable and powerful cloud service. Our framework aims at capturing hybrid systems based on a point to point message passing network of machines, with the additional capability of being able to access the services of a trusted high-performance external entity (the cloud). We focus on one concrete aspect that was not studied before, namely, ways of utilizing the cloud assistance in order to attain increased resilience against Byzantine behavior of machines in the network. Our network is modeled as a congested clique comprising $k$ machines that are completely connected to form a clique and can communicate with each other by passing small messages. In every execution, up to $\beta k$ machines (for suitable values of $\beta \in [0, 1)$) are allowed to be Byzantine, i.e., behave maliciously including colluding with each other, with the remaining $\gamma k$ or more machines being \emph{honest} (for $\gamma=1-\beta$). Additionally, the machines in our congested clique can access data through a trusted cloud via queries. This externality of the data captures many real-world distributed computing scenarios and provides a natural context for exploring Byzantine resilience for essentially all conceivable problems. Moreover, we are no longer bound by the usual limits of $\beta < 1/3$ or even $\beta < 1/2$ that are typically seen in Byzantine Agreement. We focus on a few fundamental problems. We start with the ${\textsf{Download}}$ problem, wherein the cloud stores $n$ bits and these $n$ bits must be downloaded to all of the $k$ machines. In addition to ${\textsf{Download}}$, we also consider the problem of computing the ${\textsf{Disjunction}}$ and ${\textsf{Parity}}$ of the bits in the cloud. We study these problems under several settings comprising various $\beta$ values and adversarial capabilities.

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arXiv2022

Recurrent Problems in the LOCAL model

The paper considers the SUPPORTED model of distributed computing introduced by Schmid and Suomela [HotSDN'13], generalizing the LOCAL and CONGEST models. In this framework, multiple instances of the same problem, differing from each other by the subnetwork to which they apply, recur over time, and need to be solved efficiently online. To do that, one may rely on an initial preprocessing phase for computing some useful information. This preprocessing phase makes it possible, in some cases, to overcome locality-based time lower bounds. A first contribution of the current paper is expanding the spectrum of problem types to which the SUPPORTED model applies. In addition to subnetwork-defined recurrent problems, we introduce also recurrent problems of two additional types: (i) instances defined by partial client sets, and (ii) instances defined by partially fixed outputs. Our second contribution is illustrating the versatility of the SUPPORTED framework by examining recurrent variants of three classical graph problems. The first problem is Minimum Client Dominating Set (CDS), a recurrent version of the classical dominating set problem with each recurrent instance requiring us to dominate a partial client set. We provide a constant time approximation scheme for CDS on trees and planar graphs. The second problem is Color Completion (CC), a recurrent version of the coloring problem in which each recurrent instance comes with a partially fixed coloring (of some of the vertices) that must be completed. We study the minimum number of new colors and the minimum total number of colors necessary for completing this task. The third problem we study is a recurrent version of Locally Checkable Labellings (LCL) on paths of length $n$. We show that such problems have complexities that are either $Θ(1)$ or $Θ(n)$, extending the results of Foerster et al. [INFOCOM'19].

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arXiv2022

The Power of Small Coalitions under Two-Tier Majority on Regular Graphs

In this paper, we study the following problem. Consider a setting where a proposal is offered to the vertices of a given network $G$, and the vertices must conduct a vote and decide whether to accept the proposal or reject it. Each vertex $v$ has its own valuation of the proposal; we say that $v$ is ``happy'' if its valuation is positive (i.e., it expects to gain from adopting the proposal) and ``sad'' if its valuation is negative. However, vertices do not base their vote merely on their own valuation. Rather, a vertex $v$ is a \emph{proponent} of the proposal if the majority of its neighbors are happy with it and an \emph{opponent} in the opposite case. At the end of the vote, the network collectively accepts the proposal whenever the majority of its vertices are proponents. We study this problem for regular graphs with loops. Specifically, we consider the class $\mathcal{G}_{n|d|h}$ of $d$-regular graphs of odd order $n$ with all $n$ loops and $h$ happy vertices. We are interested in establishing necessary and sufficient conditions for the class $\mathcal{G}_{n|d|h}$ to contain a labeled graph accepting the proposal, as well as conditions to contain a graph rejecting the proposal. We also discuss connections to the existing literature, including that on majority domination, and investigate the properties of the obtained conditions.

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arXiv2022

An Almost Singularly Optimal Asynchronous Distributed MST Algorithm

A singularly (near) optimal distributed algorithm is one that is (near) optimal in \emph{two} criteria, namely, its time and message complexities. For \emph{synchronous} CONGEST networks, such algorithms are known for fundamental distributed computing problems such as leader election [Kutten et al., JACM 2015] and Minimum Spanning Tree (MST) construction [Pandurangan et al., STOC 2017, Elkin, PODC 2017]. However, it is open whether a singularly (near) optimal bound can be obtained for the MST construction problem in general \emph{asynchronous} CONGEST networks. We present a randomized distributed MST algorithm that, with high probability, computes an MST in \emph{asynchronous} CONGEST networks and takes $\tilde{O}(D^{1+ε} + \sqrt{n})$ time and $\tilde{O}(m)$ messages, where $n$ is the number of nodes, $m$ the number of edges, $D$ is the diameter of the network, and $ε>0$ is an arbitrarily small constant (both time and message bounds hold with high probability). Our algorithm is message optimal (up to a polylog$(n)$ factor) and almost time optimal (except for a $D^ε$ factor). Our result answers an open question raised in Mashregi and King [DISC 2019] by giving the first known asynchronous MST algorithm that has sublinear time (for all $D = O(n^{1-ε})$) and uses $\tilde{O}(m)$ messages. Using a result of Mashregi and King [DISC 2019], this also yields the first asynchronous MST algorithm that is sublinear in both time and messages in the $KT_1$ CONGEST model. A key tool in our algorithm is the construction of a low diameter rooted spanning tree in asynchronous CONGEST that has depth $\tilde{O}(D^{1+ε})$ (for an arbitrarily small constant $ε> 0$) in $\tilde{O}(D^{1+ε})$ time and $\tilde{O}(m)$ messages. To the best of our knowledge, this is the first such construction that is almost singularly optimal in the asynchronous setting.

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arXiv2021

Singularly Near Optimal Leader Election in Asynchronous Networks

This paper concerns designing distributed algorithms that are {\em singularly optimal}, i.e., algorithms that are {\em simultaneously} time and message {\em optimal}, for the fundamental leader election problem in {\em asynchronous} networks. Kutten et al. (JACM 2015) presented a singularly near optimal randomized leader election algorithm for general {\em synchronous} networks that ran in $O(D)$ time and used $O(m \log n)$ messages (where $D$, $m$, and $n$ are the network's diameter, number of edges and number of nodes, respectively) with high probability.\footnote{Throughout, "with high probability" means "with probability at least $1-1/n^c$, for constant $c$."} Both bounds are near optimal (up to a logarithmic factor), since $Ω(D)$ and $Ω(m)$ are the respective lower bounds for time and messages for leader election even for synchronous networks and even for (Monte-Carlo) randomized algorithms. On the other hand, for general asynchronous networks, leader election algorithms are only known that are either time or message optimal, but not both. Kutten et al. (DISC 2020) presented a randomized asynchronous leader election algorithm that is singularly near optimal for \emph{complete networks}, but left open the problem for general networks. This paper shows that singularly near optimal (up to polylogarithmic factors) bounds can be achieved for general {\em asynchronous} networks. We present a randomized singularly near optimal leader election algorithm that runs in $O(D + \log^2n)$ time and $O(m\log^2 n)$ messages with high probability. Our result is the first known distributed leader election algorithm for asynchronous networks that is near optimal with respect to both time and message complexity and improves over a long line of results including the classical results of Gallager et al. (ACM TOPLAS, 1983), Peleg (JPDC, 1989), and Awerbuch (STOC 89).

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arXiv2021

Budgeted Dominating Sets in Uncertain Graphs

We study the {\em Budgeted Dominating Set} (BDS) problem on uncertain graphs, namely, graphs with a probability distribution $p$ associated with the edges, such that an edge $e$ exists in the graph with probability $p(e)$. The input to the problem consists of a vertex-weighted uncertain graph $\G=(V, E, p, ω)$ and an integer {\em budget} (or {\em solution size}) $k$, and the objective is to compute a vertex set $S$ of size $k$ that maximizes the expected total domination (or total weight) of vertices in the closed neighborhood of $S$. We refer to the problem as the {\em Probabilistic Budgeted Dominating Set}~(PBDS) problem and present the following results. \begin{enumerate} \dnsitem We show that the PBDS problem is NP-complete even when restricted to uncertain {\em trees} of diameter at most four. This is in sharp contrast with the well-known fact that the BDS problem is solvable in polynomial time in trees. We further show that PBDS is \wone-hard for the budget parameter $k$, and under the {\em Exponential time hypothesis} it cannot be solved in $n^{o(k)}$ time. \item We show that if one is willing to settle for $(1-ε)$ approximation, then there exists a PTAS for PBDS on trees. Moreover, for the scenario of uniform edge-probabilities, the problem can be solved optimally in polynomial time. \item We consider the parameterized complexity of the PBDS problem, and show that Uni-PBDS (where all edge probabilities are identical) is \wone-hard for the parameter pathwidth. On the other hand, we show that it is FPT in the combined parameters of the budget $k$ and the treewidth. \item Finally, we extend some of our parameterized results to planar and apex-minor-free graphs. \end{enumerate}

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arXiv2021

Distributed Graph Realizations

We study graph realization problems from a distributed perspective and we study it in the node capacitated clique (NCC) model of distributed computing, recently introduced for representing peer-to-peer networks. We focus on two central variants, degree-sequence realization and minimum threshold-connectivity realization both of which result in overlay network realizations. Overlay network realizations can be either explicit or implicit. Explicit realizations require both endpoints of any edge in the realized graph to be aware of the edge. In implicit realizations, on the other hand, at least one endpoint of each edge of the realized graph needs to be aware of the edge. The main realization algorithms we present are the following. 1. An $\tilde{O}(\min\{\sqrt{m},Δ\})$ time algorithm for implicit realization of a degree sequence. Here, $Δ= \max_v d(v)$ is the maximum degree and $m = (1/2) \sum_v d(v)$ is the number of edges in the final realization. An $\tilde{O}(Δ)$ time algorithm for an explicit realization of a degree sequence. We first compute an implicit realization and then transform it into an explicit one in $\tilde{O}(Δ)$ additional rounds. 2. An $\tilde{O}(Δ)$ time algorithm for the threshold connectivity problem that obtains an explicit solution and an improved $\tilde{O}(1)$ algorithm for implicit realization when all nodes know each other's IDs. These algorithms are 2-approximations w.r.t. the number of edges. We complement our upper bounds with lower bounds to show that the above algorithms are tight up to factors of $\log n$. Additionally, we provide algorithms for realizing trees and an $\tilde{O}(1)$ round algorithm for approximate degree sequence realization.

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arXiv2020

Singularly Optimal Randomized Leader Election

This paper concerns designing distributed algorithms that are singularly optimal, i.e., algorithms that are simultaneously time and message optimal, for the fundamental leader election problem in networks. Our main result is a randomized distributed leader election algorithm for asynchronous complete networks that is essentially (up to a polylogarithmic factor) singularly optimal. Our algorithm uses $O(n)$ messages with high probability and runs in $O(\log^2 n)$ time (with high probability) to elect a unique leader. The $O(n)$ message complexity should be contrasted with the $Ω(n \log n)$ lower bounds for the deterministic message complexity of leader election algorithms (regardless of time), proven by Korach, Moran, and Zaks (TCS, 1989) for asynchronous algorithms and by Afek and Gafni (SIAM J. Comput., 1991) for synchronous networks. Hence, our result also separates the message complexities of randomized and deterministic leader election. More importantly, our (randomized) time complexity of $O(\log^2 n)$ for obtaining the optimal $O(n)$ message complexity is significantly smaller than the long-standing $\tildeΘ(n)$ time complexity obtained by Afek and Gafni and by Singh (SIAM J. Comput., 1997) for message optimal (deterministic) election in asynchronous networks. In synchronous complete networks, Afek and Gafni showed an essentially singularly optimal deterministic algorithm with $O(\log n)$ time and $O(n \log n)$ messages. Ramanathan et al. (Distrib. Comput. 2007) used randomization to improve the message complexity, and showed a randomized algorithm with $O(n)$ messages and $O(\log n)$ time (with failure probability $O(1 / \log^{Ω(1)}n)$). Our second result is a tightly singularly optimal randomized algorithm, with $O(1)$ time and $O(n)$ messages, for this setting, whose time bound holds with certainty and message bound holds with high probability.

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