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Tomasz Jurdzinski

Publications and source records attributed to Tomasz Jurdzinski.

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Distributed Local Verification using Proofs with(out) Errors

We study local verification of graph properties in distributed networks under the framework of \emph{locally checkable proofs} (LCPs). In an LCP, a prover assigns proof labels to nodes, and a distributed verifier must make all nodes accept if the graph satisfies the property, while at least one node rejects otherwise. Each node bases its decision on a local neighborhood, called its \emph{view distance}. Our focus is twofold. First, we study cycle existence, i.e., whether a graph contains a cycle (as opposed to cycle-freeness). We show that cycle existence admits verification with only $3$ proof labels and view distance $1$, and establish a matching lower bound. More importantly, inspired by direction-encoding techniques based on BFS distances, we introduce a novel gadget that encodes direction using only $2$ labels and view distance $3$ through repeated occurrences of the string $001101$. Although developed for cycle existence, this gadget may be useful for other verification tasks. Second, we introduce an \emph{erroneous proof} model in which an adversary may corrupt proof labels of at most $i$ nodes within the $(2i+1)$-hop neighborhood of each node. We present an algorithmic framework, called \textbf{\texttt{refix}}, that transforms an error-free verifier into one that tolerates such errors at the cost of a view distance of $2i+1$. We demonstrate the framework on cycle existence, cycle-freeness, and bipartiteness, and establish lower bounds relating the number of errors to the required view distance. Finally, we show that our $2$-label, view-distance-$3$ verifier for cycle existence admits a $3$-round implementation in the \textsc{CONGEST} model, providing a first step toward implementing LCPs under communication constraints.

cs.DC

Optimal-Length Labeling Schemes and Fast Algorithms for k-gathering and k-broadcasting

We consider basic communication tasks in arbitrary radio networks: $k$-broadcasting and $k$-gathering. In the case of $k$-broadcasting messages from $k$ sources have to get to all nodes in the network. The goal of $k$-gathering is to collect messages from $k$ source nodes in a designated sink node. We consider these problems in the framework of distributed algorithms with advice. Krisko and Miller showed in 2021 that the optimal size of advice for $k$-broadcasting is $Θ(\min(\log Δ,$ $ \log k))$, where $Δ$ is equal to the maximum degree of a vertex of the input communication graph. We show that the same bound $Θ(\min(\log Δ, \log k))$ on the size of optimal labeling scheme holds also for the $k$-gathering problems. Moreover, we design fast algorithms for both problems with asymptotically optimal size of advice. For $k$-gathering our algorithm works in at most $D+k$ rounds, where $D$ is the diameter of the communication graph. This time bound is optimal even for centralized algorithms. We apply the $k$-gathering algorithm for $k$-broadcasting to achieve an algorithm working in time $O(D+\log^2 n+k)$ rounds. We also exhibit a logarithmic time complexity gap between distributed algorithms with advice of optimal size and distributed algorithms with distinct arbitrary labels.

cs.DS

Optimal Packet-oblivious Stable Routing in Multi-hop Wireless Networks

Stability is an important issue in order to characterize the performance of a network, and it has become a major topic of study in the last decade. Roughly speaking, a communication network system is said to be stable if the number of packets waiting to be delivered (backlog) is finitely bounded at any one time. In this paper, we introduce a new family of combinatorial structures, which we call universally strong selectors, that are used to provide a set of transmission schedules. Making use of these structures, combined with some known queuing policies, we propose a packet-oblivious routing algorithm which is working without using any global topological information, and guarantees stability for certain injection rates. We show that this protocol is asymptotically optimal regarding the injection rate for which stability is guaranteed. Furthermore, we also introduce a packet-oblivious routing algorithm that guarantees stability for higher traffic. This algorithm is optimal regarding the injection rate for which stability is guaranteed. However, it needs to use some global information of the system topology.

cs.NI

Energy Efficient Adversarial Routing in Shared Channels

We investigate routing on networks modeled as multiple access channels, when packets are injected continually. There is an energy cap understood as a bound on the number of stations that can be switched on simultaneously. Each packet is injected into some station and needs to be delivered to its destination station via the channel. A station has to be switched on in order to receive a packet when it is heard on the channel. Each station manages when it is switched on and off by way of a programmable wakeup mechanism, which is scheduled by a routing algorithm. Packet injection is governed by adversarial models that determine upper bounds on injection rates and burstiness. We develop deterministic distributed routing algorithms and assess their performance in the worst-case sense. One of the algorithms maintains bounded queues for the maximum injection rate 1 subject only to the energy cap 3. This energy cap is provably optimal, in that obtaining the same throughput with the energy cap 2 is impossible. We give algorithms subject to the minimum energy cap 2 that have latency polynomial in the total number of stations n for each fixed adversary of injection rate less than 1. An algorithm is k-energy-oblivious if at most k stations are switched on in a round and for each station the rounds when it will be switched on are determined in advance. We give a k-energy-oblivious algorithm that has packet delay O(n) for adversaries of injection rates less than (k-1)/(n-1), and show that there is no k-energy-oblivious stable algorithm against adversaries with injection rates greater than k/n. We give a k-energy-oblivious algorithm routing directly that has latency O(n^2/k) for adversaries of sufficiently small injection rates that are O(k^2/n^2). We show that no k-energy-oblivious algorithm routing directly can be stable against adversaries with injection rates greater than k(k-1)/n(n-1).

cs.DC

Routing in Wireless Networks with Interferences

We consider dynamic routing in multi-hop wireless networks with adversarial traffic. The model of wireless communication incorporates interferences caused by packets' arrivals into the same node that overlap in time. We consider two classes of adversaries: balanced and unbalanced. We demonstrate that, for each routing algorithm and an unbalanced adversary, the algorithm is unstable against this adversary in some networks. We develop a routing algorithm that has bounded packet latency against each balanced adversary.

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Deterministic Digital Clustering of Wireless Ad Hoc Networks

We consider deterministic distributed communication in wireless ad hoc networks of identical weak devices under the SINR model without predefined infrastructure. Most algorithmic results in this model rely on various additional features or capabilities, e.g., randomization, access to geographic coordinates, power control, carrier sensing with various precision of measurements, and/or interference cancellation. We study a pure scenario, when no such properties are available. As a general tool, we develop a deterministic distributed clustering algorithm. Our solution relies on a new type of combinatorial structures (selectors), which might be of independent interest. Using the clustering, we develop a deterministic distributed local broadcast algorithm accomplishing this task in $O(Δ\log^*N \log N)$ rounds, where $Δ$ is the density of the network. To the best of our knowledge, this is the first solution in pure scenario which is only polylog$(n)$ away from the universal lower bound $Ω(Δ)$, valid also for scenarios with randomization and other features. Therefore, none of these features substantially helps in performing the local broadcast task. Using clustering, we also build a deterministic global broadcast algorithm that terminates within $O(D(Δ+ \log^* N) \log N)$ rounds, where $D$ is the diameter of the network. This result is complemented by a lower bound $Ω(D Δ^{1-1/α})$, where $α> 2$ is the path-loss parameter of the environment. This lower bound shows that randomization or knowledge of own location substantially help (by a factor polynomial in $Δ$) in the global broadcast. Therefore, unlike in the case of local broadcast, some additional model features may help in global broadcast.

cs.DS

MST in O(1) Rounds of the Congested Clique

We present a distributed randomized algorithm finding Minimum Spanning Tree (MST) of a given graph in O(1) rounds, with high probability, in the Congested Clique model. The input graph in the Congested Clique model is a graph of n nodes, where each node initially knows only its incident edges. The communication graph is a clique with limited edge bandwidth: each two nodes (not necessarily neighbours in the input graph) can exchange $O(\log n)$ bits. As in previous works, the key part of the MST algorithm is an efficient Connected Components (CC) algorithm. However, unlike the former approaches, we do not aim at simulating the standard Boruvka algorithm, at least at initial stages of the CC algorithm. Instead, we develop a new technique which combines connected components of sample sparse subgraphs of the input graph in order to accelerate the process of uncovering connected components of the original input graph. More specifically, we develop a sparsification technique which reduces an initial CC problem in $O(1)$ rounds to its two restricted instances. The former instance has a graph with maximal degree $O(\log \log n)$ as the input -- here our sample-combining technique helps. In the latter instance, a partition of the input graph into $O(n/\log \log n)$ connected components is known. This gives an opportunity to apply previous algorithms to determine connected components in $O(1)$ rounds. Our result addresses the problem from and the $O(\log \log n)$ algorithm of Lotker et al. [SPAA 2003; SICOMP 2005], improves over previous $O(\log* n)$ algorithm of Ghaffari et al. [PODC 2016] and $O(\log \log \log n)$ algorithm of Hegeman et al. [PODC 2015] . It also determines $Θ(1)$ round complexity in the congested clique for MST, as well as other graph problems, including bipartiteness, cut verification, s-t connectivity and cycle containment.

cs.DC

Patrolling a Path Connecting a Set of Points with Unbalanced Frequencies of Visits

Patrolling consists of scheduling perpetual movements of a collection of mobile robots, so that each point of the environment is regularly revisited by any robot in the collection. In previous research, it was assumed that all points of the environment needed to be revisited with the same minimal frequency. In this paper we study efficient patrolling protocols for points located on a path, where each point may have a different constraint on frequency of visits. The problem of visiting such divergent points was recently posed by Gasieniec et al. in [13], where the authors study protocols using a single robot patrolling a set of $n$ points located in nodes of a complete graph and in Euclidean spaces. The focus in this paper is on patrolling with two robots. We adopt a scenario in which all points to be patrolled are located on a line. We provide several approximation algorithms concluding with the best currently known $\sqrt 3$-approximation.

cs.DC

MSF and Connectivity in Limited Variants of the Congested Clique

The congested clique is a synchronous, message-passing model of distributed computing in which each computational unit (node) in each round can send message of O(log n) bits to each other node of the network, where n is the number of nodes. This model has been considered under two extreme scanarios: unicast or broadcast. In the unicast model, a node can send (possibly) different message to each other node of the network. In contrast, in the broadcast model each node sends a single (the same) message to all other nodes. We study the congested clique model parametrized by the range r, the maximum number of different messages a node can send in one round. Following recent progress in design of algorihms for graph connectivity and minimum span- ning forest (MSF) in the unicast congested clique, we study these problems in limited variants of the congested clique. We present the first sub-logarithmic algorithm for connected components in the broadcast congested clique. Then, we show that efficient unicast deterministic algorithm for MSF and randomized algorithm for connected components can be efficiently imple- mented in the rcast model with range r = 2, the weakest model of the congested clique above the broadcast variant (r = 1) in the hierarchy with respect to range. More importantly, our al- gorithms give the first solutions with optimal capacity of communication edges, while preserving small round complexity.

cs.DC

Deterministic Symmetry Breaking in Ring Networks

We study a distributed coordination mechanism for uniform agents located on a circle. The agents perform their actions in synchronised rounds. At the beginning of each round an agent chooses the direction of its movement from clockwise, anticlockwise, or idle, and moves at unit speed during this round. Agents are not allowed to overpass, i.e., when an agent collides with another it instantly starts moving with the same speed in the opposite direction (without exchanging any information with the other agent). However, at the end of each round each agent has access to limited information regarding its trajectory of movement during this round. We assume that $n$ mobile agents are initially located on a circle unit circumference at arbitrary but distinct positions unknown to other agents. The agents are equipped with unique identifiers from a fixed range. The {\em location discovery} task to be performed by each agent is to determine the initial position of every other agent. Our main result states that, if the only available information about movement in a round is limited to %information about distance between the initial and the final position, then there is a superlinear lower bound on time needed to solve the location discovery problem. Interestingly, this result corresponds to a combinatorial symmetry breaking problem, which might be of independent interest. If, on the other hand, an agent has access to the distance to its first collision with another agent in a round, we design an asymptotically efficient and close to optimal solution for the location discovery problem.

cs.DC

On the Impact of Geometry on Ad Hoc Communication in Wireless Networks

In this work we address the question how important is the knowledge of geometric location and network density to the efficiency of (distributed) wireless communication in ad hoc networks. We study fundamental communication task of broadcast and develop well-scalable, randomized algorithms that do not rely on GPS information, and which efficiency formulas do not depend on how dense the geometric network is. We consider two settings: with and without spontaneous wake-up of nodes. In the former setting, in which all nodes start the protocol at the same time, our algorithm accomplishes broadcast in $O(D\log n + \log^2 n)$ rounds under the SINR model, with high probability (whp), where $D$ is the diameter of the communication graph and $n$ is the number of stations. In the latter setting, in which only the source node containing the original message is active in the beginning, we develop a slightly slower algorithm working in $O(D\log^2 n)$ rounds whp. Both algorithms are based on a novel distributed coloring method, which is of independent interest and potential applicability to other communication tasks under the SINR wireless model.

cs.DC

Online Packet Scheduling under Adversarial Jamming

We consider the problem of scheduling packets of different lengths via a directed communication link prone to jamming errors. Dynamic packet arrivals and errors are modelled by an adversary. We focus on estimating relative throughput of online scheduling algorithms, that is, the ratio between the throughputs achieved by the algorithm and the best scheduling for the same arrival and error patterns. This framework allows more accurate analysis of performance of online scheduling algorithms, even in worst-case arrival and error scenarios. We design an online algorithm for scheduling packets of arbitrary lengths, achieving optimal relative throughput in the range (1/3,1/2] (the exact value depends on packet lengths). In other words, for any arrival and jamming patterns, our solution gives throughput which is no more than c times worse than the best possible scheduling for these patters, where c in [2; 3) is the inverse of relative throughput. Another algorithm we design makes use of additional resources in order to achieve relative throughput 1, that is, it achieves at least as high throughput as the best schedule without such resources, for any arrival and jamming patterns. More precisely, we show that if the algorithm can run with double speed, i.e., with twice higher frequency, then its relative throughput is 1. This demonstrates that throughput of the best online scheduling algorithms scales well with resource augmentation. Keywords: Packet scheduling, Dynamic packet arrivals, Adversarial jamming, Online algorithms, Relative throughput, Resource augmentation.

cs.DC

Distributed Broadcasting in Wireless Networks under the SINR Model

In the advent of large-scale multi-hop wireless technologies, such as MANET, VANET, iThings, it is of utmost importance to devise efficient distributed protocols to maintain network architecture and provide basic communication tools. One of such fundamental communication tasks is broadcast, also known as a 1-to-all communication. We propose several new efficient distributed algorithms and evaluate their time performance both theoretically and by simulations. First randomized algorithm accomplishes broadcast in O(D+log(1/d)) rounds with probability at least 1-d on any uniform-power network of n nodes and diameter D, when equipped with local estimate of network density. Additionally, we evaluate average performance of this protocols by simulations on two classes of generated networks - uniform and social - and compare the results with performance of exponential backoff heuristic. Ours is the first provably efficient and well-scalable distributed solution for the (global) broadcast task. The second randomized protocol developed in this paper does not rely on the estimate of local density, and achieves only slightly higher time performance O((D+log(1/d))log n). Finally, we provide a deterministic algorithm achieving similar time O(D log^2 n), supported by theoretical analysis.

cs.DC

Distributed Deterministic Broadcasting in Wireless Networks of Weak Devices under the SINR Model

In this paper we initiate a study of distributed deterministic broadcasting in ad-hoc wireless networks with uniform transmission powers under the SINR model. We design algorithms in two settings: with and without local knowledge about immediate neighborhood. In the former setting, our solution has almost optimal O(Dlog2 n) time cost, where n is the size of a network, D is the eccentricity of the network and {1,...,N} is the set of possible node IDs. In the latter case, we prove an Omega(n log N) lower bound and develop an algorithm matching this formula, where n is the number of network nodes. As one of the conclusions, we derive that the inherited cost of broadcasting techniques in wireless networks is much smaller, by factor around min{n/D,Delta}, than the cost of learning the immediate neighborhood. Finally, we develop a O(D Delta log2 N) algorithm for the setting without local knowledge, where Delta is the upper bound on the degree of the communication graph of a network. This algorithm is close to a lower bound Omega(D Delta).

cs.DC

Distributed Deterministic Broadcasting in Uniform-Power Ad Hoc Wireless Networks

Development of many futuristic technologies, such as MANET, VANET, iThings, nano-devices, depend on efficient distributed communication protocols in multi-hop ad hoc networks. A vast majority of research in this area focus on design heuristic protocols, and analyze their performance by simulations on networks generated randomly or obtained in practical measurements of some (usually small-size) wireless networks. %some library. Moreover, they often assume access to truly random sources, which is often not reasonable in case of wireless devices. In this work we use a formal framework to study the problem of broadcasting and its time complexity in any two dimensional Euclidean wireless network with uniform transmission powers. For the analysis, we consider two popular models of ad hoc networks based on the Signal-to-Interference-and-Noise Ratio (SINR): one with opportunistic links, and the other with randomly disturbed SINR. In the former model, we show that one of our algorithms accomplishes broadcasting in $O(D\log^2 n)$ rounds, where $n$ is the number of nodes and $D$ is the diameter of the network. If nodes know a priori the granularity $g$ of the network, i.e., the inverse of the maximum transmission range over the minimum distance between any two stations, a modification of this algorithm accomplishes broadcasting in $O(D\log g)$ rounds. Finally, we modify both algorithms to make them efficient in the latter model with randomly disturbed SINR, with only logarithmic growth of performance. Ours are the first provably efficient and well-scalable, under the two models, distributed deterministic solutions for the broadcast task.

cs.DC

Distributed backbone structure for deterministic algorithms in the SINR model of wireless networks

The Signal-to-Interference-and-Noise-Ratio (SINR) physical model is one of the legitimate models of wireless networks. Despite of the vast amount of study done in design and analysis of centralized algorithms supporting wireless communication under the SINR physical model, little is known about distributed algorithms in this model, especially deterministic ones. In this work we construct, in a deterministic distributed way, a backbone structure on the top of a given wireless network, which can be used for transforming many algorithms designed in a simpler model of ad hoc broadcast networks without interference into the SINR physical model with uniform power of stations, without increasing their asymptotic time complexity. The time cost of the backbone data structure construction is only O(Delta polylog n) rounds, where Delta is roughly the inverse of network density and n is the number of nodes in the whole network. The core of the construction is a novel combinatorial structure called SINR-selector, which is introduced and constructed in this paper. We demonstrate the power of the backbone data structure by using it for obtaining efficient O(D+Delta polylog n)-round and O(D+k+Delta polylog n)-round deterministic distributed solutions for leader election and multi-broadcast, respectively, where D is the network diameter and k is the number of messages to be disseminated.

cs.DC