In the distributed localisation problem (DLP), n anonymous robots (agents) A_0, ..., A_{n-1} are located at arbitrary points p_0, ..., p_{n-1} ∈ S, where S is a Euclidean space. Initially, each agent A_i operates within its own coordinate system in S, which may be inconsistent with those of other agents. The primary goal in DLP is for agents to reach a consensus on a unified (jointly agreed) coordinate system, in which all agents receive unique labels (coordinates) that accurately reflect the relative distances between all points p_0, ..., p_{n-1} in S. Extensive research on DLP has primarily focus on the feasibility and complexity of achieving consensus when agents have limited access to inter-agent distances, often due to missing or imprecise data. In contrast, this paper proposes a minimalist, computationally efficient distributed computing model where agents can query any pairwise relative positions, if needed. Specifically, we introduce a novel variant of population protocols, referred to as the spatial population protocols model. In this variant each agent can memorise one or a fixed number of coordinates, and when agents A_i and A_j interact, they can not only exchange their current knowledge but also either determine the distance d_{ij} between them in S (distance query model) or obtain the vector v_{ij} spanning points p_i and p_j (vector query model). We propose and analyse several distributed localisation protocols, including: 1) Leader-based localisation protocol with distance queries We propose and analyse two leader-based localisation protocols that stabilise silently in o(n) time. These protocols leverage an efficient solution to the novel concept of multi-contact epidemic, a natural generalisation of the core communication tool in population protocols, known as the one-way epidemic. 2) Self-stabilising leader localisation protocol with distance queries We show how to effectively utilise a leader election mechanism within the leader-based localisation protocol to get a DLP protocol that self-stabilises silently in time O(n(log n/n)^{1/(k+1)}log n) in k-dimensions. 3) Self-stabilising localisation protocol with vector queries We propose and analyse an optimally fast DLP protocol which self-stabilises silently in O(log n) time.

We study leader election problem via ranking within self-stabilising population protocols. In this scenario, the agent's state space comprises n rank states and x extra states. The initial configuration of n agents consists of arbitrary arrangements of rank and extra states, with the objective of self-ranking. Specifically, each agent is tasked with stabilising in a unique rank state silently, implying that after stabilisation, each agent remains in its designated state indefinitely.

In this paper we consider a known variant of the standard population protocol model in which agents can be connected by edges, referred to as the network constructor model. During an interaction between two agents the relevant connecting edge can be formed, maintained or eliminated by the transition function. The state space of agents is fixed (constant size) and the size n of the population is not known, i.e., not hard-coded in the transition function. Since pairs of agents are chosen uniformly at random the status of each edge is updated every Θ(n²) interactions in expectation which coincides with Θ(n) parallel time. This phenomenon provides a natural lower bound on the time complexity for any non-trivial network construction designed for this variant. This is in contrast with the standard population protocol model in which efficient protocols operate in O(polylog n) parallel time. The main focus in this paper is on efficient manipulation of linear structures including formation, self-replication and distribution (including pipelining) of complex information in the adopted model. - We propose and analyse a novel edge based phase clock counting parallel time Θ(nlog n) in the network constructor model, showing also that its leader based counterpart provides the same time guaranties in the standard population protocol model. Note that all currently known phase clocks can count parallel time not exceeding O(polylog n). - The new clock enables a nearly optimal O(nlog n) parallel time spanning line construction (a key component of universal network construction), which improves dramatically on the best currently known O(n²) parallel time protocol, solving the main open problem in the considered model [O. Michail and P. Spirakis, 2016]. - We propose a new probabilistic bubble-sort algorithm in which random comparisons and transfers are allowed only between the adjacent positions in the sequence. Utilising a novel potential function reasoning we show that rather surprisingly this probabilistic sorting (via conditional pipelining) procedure requires O(n²) comparisons in expectation and whp, and is on par with its deterministic counterpart. - We propose the first population protocol allowing self-replication of a strand of an arbitrary length k (carrying a k-bit message of size independent of the state space) in parallel time O(n(k+log n)). The pipelining mechanism and the time complexity analysis of the strand self-replication protocol mimic those used in the probabilistic bubble-sort. The new protocol permits also simultaneous self-replication, where l copies of the strand can be created in time O(n(k+log n)log l). Finally, we discuss application of the strand self-replication protocol to pattern matching. Our protocols are always correct and provide time guaranties with high probability defined as 1-n^{-η}, for a constant η > 0.

We study population protocols, a model of distributed computing appropriate for modeling well-mixed chemical reaction networks and other physical systems where agents exchange information in pairwise interactions, but have no control over their schedule of interaction partners. The majority problem is that of determining in an initial population of$n$agents, each with one of two opinions$A$or B, whether there are more A, more B, or a tie. A stable protocol solves this problem with probability 1 by eventually entering a configuration in which all agents agree on a correct consensus decision of A, B, or T, from which the consensus cannot change. We describe a protocol solving this problem using O(log n) states (log log$n$+ O(1) bits of memory) and optimal expected time$O$(log$n$). The number of states$O$(log$n$) is known to be optimal for polylogarithmic time stable protocols that are “output dominant” and “monotone” [1]. These are two natural constraints satisfied by our protocol, making it simultaneously time- and state-optimal for that class. We introduce a key technique called a “fixed resolution clock” to achieve partial synchronization. Our protocol is nonuniform: the transition function has the value [log$n$] encoded in it. We show that the protocol can be modified to be uniform, while increasing the state complexity to Θ (log$n$log log n).

This paper studies the Contention resolution problem on a shared channel (also known as a multiple access channel). A set of$n$stations are connected to a common device and are able to communicate by transmitting and listening. Each station may have a message to broadcast. At any round, a transmission is successful if and only if exactly one station is transmitting at that round. Simultaneous transmissions interfere one another and, as a result, the respective messages are lost. The Contention resolution is the fundamental problem of scheduling the transmissions into rounds in such a way that any station delivers successfully its message on the channel. We consider a general dynamic distributed setting. We assume that the stations can join (or be activated on) the channel at arbitrary times (dynamic scenario). This has to be contrasted with the simplified static scenario, in which all stations are assumed to be activated simultaneously. We also assume that the stations are not able to detect whether a collision among simultaneous transmissions occurred (model without collision detection). Finally, there is no global clock in the system: each station measures the time using its own local clock which starts when the station is activated and is possibly out of sync with respect to the other stations. We study non-adaptive deterministic distributed algorithms for the contention resolution problem and assess their efficiency both in terms of channel utilization (also called throughput) and energy consumption. While this topic has been quite extensively examined for randomized algorithms, this is, to the best of our knowledge, the first paper to discuss to which extent deterministic contention resolution algorithms can be efficient in terms of both channel utilization and energy consumption. Our results imply an exponential separation gap between static and dynamic setting with respect to channel utilization. We also show that the knowledge of the number of participating stations k (or an upper bound on it) has a substantial impact on the energy consumption.

We study population protocols, a model of distributed computing where agents exchange information in pairwise interactions, but have no control over their schedule of interaction partners. The well-studied majority problem is that of determining in an initial population of n agents, each with one of two opinions A or B, whether there are more A, more B, or a tie. A stable protocol solves this problem with probability 1 by eventually entering a configuration in which all agents agree on a correct consensus decision of A, B, or T, from which the consensus cannot change. We describe a protocol that solves this problem using O(log n) states (log log n + O(1) bits of memory) and optimal expected time O(log n). The number of states O(log n) is known to be optimal for the class of polylogarithmic time stable protocols that are "output dominant'' and "monotone''. These are two natural constraints satisfied by our protocol, making it simultaneously time- and state-optimal for that class. Our protocol is nonuniform : the transition function has the value log n encoded in it. We show that the protocol can be modified to be uniform, while increasing the state complexity to Θ(log n log log n).

The model of population protocols refers to the growing in popularity theoretical framework suitable for studying pairwise interactions within a large collection of simple indistinguishable entities, frequently called agents . In this article, the emphasis is on the space complexity of fast leader election in population protocols governed by the random scheduler , which uniformly at random selects pairwise interactions between n agents. One of the main results of this article is the first fast space optimal leader election protocol , which works with high probability. The new protocol operates in parallel time O (log 2 n ) equivalent to O ( n log 2 n ) sequential pairwise interactions with each agent’s memory space limited to O (log log n ) states. This double logarithmic space utilisation matches asymptotically the lower bound ½log log n on the number of states utilised by agents in any leader election algorithm with the running time o ( n \polylog n ); see Reference [7]. Our new solution expands also on the classical concept of phase clocks used to synchronise and to coordinate computations in distributed algorithms. In particular, we formalise the concept and provide a rigorous analysis of phase clocks operating in nested modes. Our arguments are also valid for phase clocks propelled by multiple leaders. The combination of the two results in the first time-space efficient leader election algorithm. We also provide a complete formal argumentation, indicating that our solution is always correct, fast, and it works with high probability.

A shared communication channel (also known as a multiple access channel) is among the most popular and widely studied models of communication and distributed computing. In this model, stations are able to communicate by transmitting and listening to a shared channel. A fundamental problem, called contention resolution, is to allow any station to successfully deliver its message by resolving the conflicts that arise when several stations transmit simultaneously on the channel. Despite a long history, many fundamental questions remain open in the realistic scenario when up to k stations out of n join the channel at different times. In this work we explore the impact of asynchrony, knowledge (or linear estimate) of contenders, and acknowledgments, on latency and channel utilization of non-adaptive deterministic algorithms. We show that if the number of contenders k (or a linear upper bound on it) is known and the stations switch-off after acknowledgment of their successful transmissions, the channel admits efficient solutions. In the same settings, we show that the ignorance of contention k makes the channel nearly quadratically less efficient, even if the stations could switch-off after acknowledgments. We present an algorithm which nearly matches this complexity (for unknown k) which is achieved even if acknowledgments are not provided. We show how the above algorithm could be further improved if stations could switch off upon acknowledgment. Surprisingly, our results imply an exponential impact of knowledge of contention on deterministic utilization of asynchronous channel by deterministic algorithms - it is known that for synchronized channel this feature does not influence asymptotically the channel utilization. The second implication concerns the impact of acknowledgments - they exponentially improve deterministic channel utilization if (some estimate of) k is known, unlike in the case of randomized algorithms where the improvement is only polynomial, while they are not particularly helpful in case of unknown contention. Finally, note that non-adaptive algorithms use fixed transmission schedules, which could be naturally translate into codes in the radio or beeping model - in this context our results indicate under which conditions such codes could be efficient.

The model of population protocols refers to a large collection of simple indistinguishable entities, frequently called \em agents. The agents communicate and perform computation through pairwise interactions. We study fast and space efficient leader election in population of cardinality n governed by a random scheduler, where during each time step the scheduler uniformly at random selects for interaction exactly one pair of agents. We present the first $o(łog^2)$-time leader election protocol. It operates in expected parallel time $\bigo(łog nłogłog n)$ which is equivalent to $\bigo(n łog nłogłog n)$ pairwise interactions. This is the fastest currently known leader election algorithm in which each agent utilises asymptotically optimal number of $\bigo(łogłog n)$ states. The new protocol incorporates and amalgamates successfully the power of assorted \em synthetic coins with variable rate \em phase clocks.

We consider deterministic distributed communication in wireless ad hoc networks of identical devices in the SINR model without predefined infrastructure. Most algorithmic results in this model rely on additional features or capabilities, e.g., randomization, access to geographic coordinates, power control, carrier sensing with various precision of measurements, and interference cancellation. We study a pure scenario, when no such features are available.

The model of population protocols refers to the growing in popularity theoretical framework suitable for studying pairwise interactions within a large collection of simple indistinguishable entities, frequently called agents. In this paper the emphasis is on the space complexity in fast leader election via population protocols governed by the random scheduler, which uniformly at random selects pairwise interactions from the population of n agents. The main result of this paper is a new fast and space optimal leader election protocol. The new protocol operates in parallel time O(log2 n) equivalent to O(n log2 n) sequential pairwise interactions, in which each agent utilises O(log log n) states. This double logarithmic space utilisation matches asymptotically the lower bound ½ log log n on the number of states utilised by agents in any leader election algorithm with the running time , see [7]. Our solution relies on the concept of phase clocks, a fundamental synchronisation and coordination tool in the field of Distributed Computing. We propose a new fast and robust population protocol for initialisation of phase clocks to be run simultaneously in multiple modes and intertwined with the leader election process. We also provide the reader with the relevant formal argumentation indicating that our solution is always correct and fast with high probability.

A shared channel, also called multiple-access channel, is one of the fundamental communication models. Autonomous entities communicate over a shared medium, and one of the main challenges is how to efficiently resolve collisions occurring when more than one entity attempts to access the channel at the same time. In this work we explore the impact of asynchrony, knowledge (or linear estimate) of the number of contenders, and acknowledgments, on both latency and channel utilization for the Contention resolution problem with non-adaptive deterministic algorithms.

In this work we address the question whether a simple shared channel could be efficiently utilized, that is, with a constant throughput and linear packet latency. A shared channel (also called a multiple access channel), introduced nearly 50 years ago in the context of the Ethernet [36], is among the most popular and widely studied models of communication and distributed computing. In a nutshell, a number of stations is able to communicate by transmitting and listening to a shared channel, and a message is successfully delivered to all stations if and only if its source station is the only transmitter at a time. Despite of a vast amount of work in the last decades, many fundamental questions remain open, such as: What is the impact of asynchrony on channel utilization? How important is the knowledge/estimate of the number of contenders? Could non-adaptive protocols (i.e., random codes) be asymptotically as efficient as adaptive protocols? In this work we present a broad picture of results answering the above mentioned questions for a fundamental problem of contention resolution, in which each of the contending stations needs to broadcast successfully its message. We show that adaptive algorithms or algorithms with the knowledge of contention size k (i.e., random codes with knowledge of k) achieve constant channel throughput and linear message latency even for very weak channels, i.e., with feedback restricted to simple acknowledgments and in the absence of synchronization. This asymptotically optimal performance cannot be extended to other settings --- we prove that there is no non-adaptive algorithm without the knowledge of contention size k achieving throughput \omega((\log\log k)^2/(\log k)) and/or admitting latency o(k\log k/(\log\log k)^2). This means, in particular, that coding (even random) with acknowledgments is not very efficient on a shared channel without synchronization or estimate of contention size. We also present a non-adaptive algorithm with no knowledge of contention size that almost matches these two complexities. More specifically, it achieves latency O(k\log^2 k) and channel utilization \Omega(1/\log^2 k) even if stations do not switch off after successful transmissions (and thus, could disturb other stations in succeeding), and could be improved by factor \Theta(\log\log k) if stations switch off after acknowledgment. Despite the absense of a collision detection mechanism, our algorithms are also efficient in terms of energy. The maximum number of channel accesses (including transmissions and listenings) for our non-adaptive solutions, with and without knowledge of k, is respectively O(\log k) and O(\log^2 k) whp. Regarding the adaptive algorithm, we argue that a simple modification of our protocol preserves constant throughput and linear latency while achieving O(\log k) maximum number of channel accesses per station whp.

In this paper we study space-efficient deterministic population protocols for several variants of the majority problem including plurality consensus. We focus on space efficient majority protocols in populations with an arbitrary number of colours C represented by k-bit labels, where k = ceiling (log C). In particular, we present asymptotically space-optimal (with respect to the adopted k-bit representation of colours) protocols for (1) the absolute majority problem, i.e., a protocol which decides whether a single colour dominates all other colours considered together, and (2) the relative majority problem, also known in the literature as plurality consensus, in which colours declare their volume superiority versus other individual colours. The new population protocols proposed in this paper rely on a dynamic formulation of the majority problem in which the colours originally present in the population can be changed by an external force during the communication process. The considered dynamic formulation is based on the concepts studied by D. Angluin et al. and O. Michail et al. about stabilizing inputs and composition of population protocols. Also, the protocols presented in this paper use a composition of some known protocols for static and dynamic majority.

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 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 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.

This paper studies the task of setting up ad hoc wireless networks. In such networks, it is often the case that nodes become active at different times, without coordination or knowledge about network topology. We consider the following tasks: wake-up, clock synchronization, leader election, and multimessage broadcast. We show how to achieve these goals in scalable O(D polylog(n)) time. As a tool we define and give a solution to a quasi-backbone problem, which aims to set up transmission probabilities at nodes in a way that they can be efficiently used to solve other tasks. Our results are obtained by minimalistic algorithms, which do not require power control or carrier sensing capabilities, use very small energy, local computation and memory. Moreover, unlike many previous work, they remain scalable even if the network is not highly connected.

Multiple access channel is a communication model in which many users, also called stations, could exchange information. Since it offers limited capacity, some information sent through it might be lost due to signal interference (collision). Therefore, successful message delivery to a station requires breaking symmetry on the channel. In this work we consider the channel-synchronization problem on non-synchronized channels: assuming stations with messages wake-up dynamically on the channel, what is the minimum (expected) time needed for all stations to receive at least one message each.

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 + log2 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 log2 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.

We consider online competitive algorithms for the problem of collecting weighted items from a dynamic queue S . The content of S varies over time. An update to S can occur between any two consecutive time steps, and it consists in deleting any number of items at the front of S and inserting other items into arbitrary locations in S . At each time step we are allowed to collect one item in S . The objective is to maximize the total weight of collected items. This is a generalization of bounded-delay packet scheduling (also known as buffer management). We present several upper and lower bounds on the competitive ratio for the general case and for some restricted variants of this problem.

We consider the problem of collecting weighted items from a dynamic queue . Before each step, some items at the front of can be deleted and some other items can be added to at any place. An item, once deleted, cannot be re-inserted — in other words, it “expires”. We are allowed to collect one item from per step. Each item can be collected only once. The objective is to maximize the total weight of the collected items. We study the online version of the dynamic queue problem. It is quite easy to see that the greedy algorithm that always collects the maximum-value item is 2-competitive, and that no deterministic online algorithm can be better than 1.618-competitive. We improve both bounds: We give a 1.89-competitive algorithm for general dynamic queues and we show a lower bound of 1.632 on the competitive ratio. We also provide other upper and lower bounds for restricted versions of this problem. The dynamic queue problem is a generalization of the well-studied buffer management problem, and it is an abstraction of the buffer management problem for network links with intermittent access.

This paper proves that if a poset Q has an even number of linear extensions and these extensions can be generated by adjacent transpositions, then linear extensions of union of poset Q and an arbitrary poset P can also be generated by adjacent transpositions. This result is then applied to posets P and Q, which are sums of disjoint chains.