Perfect Information Leader Election in log*n+O(1) Rounds

Distributed Computing, 2019

This paper focuses on studying the message complexity of implicit leader election in synchronous distributed networks of diameter two. Kutten et al. (J ACM 62(1):7:1-7:27, 2015) showed a fundamental lower bound of Ω(m) (m is the number of edges in the network) on the message complexity of (implicit) leader election that applied also to Monte Carlo randomized algorithms with constant success probability; this lower bound applies for graphs that have diameter at least three. On the other hand, for complete graphs (i.e., graphs with diameter one), Kutten et al. (Theor Comput Sci 561(Part B):134-143, 2015) established a tight bound ofΘ(√ n) on the message complexity of randomized leader election (n is the number of nodes in the network). For graphs of diameter two, the complexity was not known. In this paper, we settle this complexity by showing a tight bound ofΘ(n) on the message complexity of leader election in diameter-two networks. We first give a simple randomized Monte-Carlo leader election algorithm that with high probability (i.e., probability at least 1 − n −c , for some fixed positive constant c) succeeds and uses O(n log 3 n) messages and runs in O(1) rounds; this algorithm works without knowledge of n (and hence needs no global knowledge). We then show that any algorithm (even Monte Carlo randomized algorithms with large enough constant success probability) needs Ω(n) messages (even when n is known), regardless of the number of rounds. We also present an O(n log n) message deterministic algorithm that takes O(log n) rounds (but needs knowledge of n); we show that this message complexity is tight for deterministic algorithms. Together with the two previous results of Kutten et al., our results fully characterize the message complexity of leader election vis-à-vis the graph diameter.

Lecture Notes in Computer Science, 2013

This paper focuses on compact deterministic self-stabilizing solutions for the leader election problem. When the solution is required to be silent (i.e., when the state of each process remains fixed from some point in time during any execution), there exists a lower bound of Ω(log n) bits of memory per participating node , where n denotes the number of nodes in the system. This lower bound holds even in rings. We present a new deterministic (nonsilent) self-stabilizing protocol for n-node rings that uses only O(log log n) memory bits per node, and stabilizes in O(n log 2 n) rounds. Our protocol has several attractive features that make it suitable for practical purposes. First, it assumes an execution model that is used by existing compilers for real networks. Second, the size of the ring (or any upper bound on this size) does not need to be known by any node. Third, the node identifiers can be of various sizes. Finally, no synchrony assumption, besides weak fairness, is assumed. Our result shows that, perhaps surprisingly, silence can be traded for an exponential decrease in memory space without significantly increasing stabilization time or introducing restrictive assumptions.

We consider the problem of electing a leader among nodes in a highly dynamic network where the adversary has unbounded capacity to insert and remove nodes (including the leader) from the network and change connectivity at will. We present a randomized algorithm that (re)elects a leader in O(D log n) rounds with high probability, where D is a bound on the dynamic diameter of the network and n is the maximum number of nodes in the network at any point in time. We assume a model of broadcast-based communication where a node can send only 1 message of O(log n) bits per round and is not aware of the receivers in advance. Thus, our results also apply to mobile wireless adhoc networks, improving over the optimal (for deterministic algorithms) O(Dn) solution presented at FOMC 2011. We show that our algorithm is optimal by proving that any randomized Las Vegas algorithm takes at least Ω(D log n) rounds to elect a leader with high probability, which shows that our algorithm yields the best possible (up to constants) termination time.

We start with a set of n players. With some probability $P(n, k)$, we kill $n−k$ players; the other ones stay alive, and we repeat with them. What is the distribution of the number $X_n$ of phases (or rounds) before getting only one player? We present a probabilistic analysis of this algorithm under some conditions on the probability distributions $P(n, k)$, including stochastic monotonicity and the assumption that roughly a fixed proportion $\alpha$ of the players survive in each round. We prove a kind of convergence in distribution for $\lceilX_n−\log_{1/\alpha}(n)\rceil$; as in many other similar problems there are oscillations and no true limit distribution, but suitable subsequences converge, and there is an absolutely continuous random variable $Z$ such that $d(Xn, \lceilZ+\log_{1/\alpha}(n)\rceil) \to 0$, where d is either the total variation distance or the Wasserstein distance. Applications of the general result include the leader election algorithm where players are elimin...

Algorithmica, 2018

Leader election is one of the basic problems in distributed computing. This is a symmetry breaking problem: all nodes of a network must agree on a single node, called the leader. If the nodes of the network have distinct labels, then such an agreement means that all nodes have to output the label of the elected leader. For anonymous networks, the task of leader election is formulated as follows: every node v of the network must output a simple path, which is coded as a sequence of port numbers, such that all these paths end at a common node, the leader. In this paper, we study deterministic leader election in arbitrary anonymous networks. It is well known that leader election is impossible in some networks, regardless of the allocated amount of time, even if nodes know the map of the network. This is due to possible symmetries in it. However, even in networks in which it is possible to elect a leader knowing the map, the task may be still impossible without any knowledge, regardless of the allocated time. On the other hand, for any network in which leader election is possible knowing the map, there is a minimum time, called the election index, in which this can be done. Informally, the election index of a network is the minimum depth at which views of all nodes are distinct. Our aim is to establish tradeoffs between the allocated time τ and the amount of information that has to be given a priori to the nodes to enable leader election in time τ in all networks for which leader election in this time is at all possible. Following the framework of algorithms with advice, this information (a single binary string) is provided to all nodes at the start by an oracle knowing the entire network. The length of this string is called the size of advice. For a given time τ allocated to leader election, we give upper and lower bounds on the minimum size of advice sufficient to perform leader election in time τ. We focus on the two sides of the time spectrum. For the smallest possible time, which is the election index of the network, we show that the minimum size of advice is linear in the size n of the network, up to polylogarithmic factors. On the other hand, we consider large values of time: larger than the diameter D by a summand, respectively, linear, polynomial, and exponential in the election index; for these values, we prove tight bounds on the minimum size of advice, up to multiplicative constants. We also show that constant advice is not sufficient for leader election in all graphs, regardless of the allocated time.

Proceedings of the 2013 ACM symposium on Principles of distributed computing, 2013

Electing a leader is a fundamental task in distributed computing. In its implicit version, only the leader must know who is the elected leader. This paper focuses on studying the message and time complexity of randomized implicit leader election in synchronous distributed networks. Surprisingly, the most "obvious" complexity bounds have not been proven for randomized algorithms. In particular, the seemingly obvious lower bounds of Ω(m) messages, where m is the number of edges in the network, and Ω(D) time, where D is the network diameter, are non-trivial to show for randomized (Monte Carlo) algorithms. (Recent results, showing that even Ω(n), where n is the number of nodes in the network, is not a lower bound on the messages in complete networks, make the above bounds somewhat less obvious). To the best of our knowledge, these basic lower bounds have not been established even for deterministic algorithms, except for the restricted case of comparison algorithms, where it was also required that nodes may not wake up spontaneously and that D and n were not known. We establish these fundamental lower bounds in this paper for the general case, even for randomized Monte Carlo algorithms. Our lower bounds are universal in the sense that they hold for all universal algorithms (namely, algorithms that work for all graphs), apply to every D, m, and n, and hold even if D, m, and n are known, all the nodes wake up simultaneously, and the algorithms can make any use of node's identities. To show that these bounds are tight, we present an O(m) messages algorithm. An O(D) time leader election algorithm is known. A slight adaptation of * A preliminary version of this article appeared in the proceedings of the 32nd ACM Symposium on Principles of Distributed Computing (PODC) 2013, pages 100-109.

Theoretical Computer Science, 2006

Itai and Rodeh showed that, on the average, the communication of a leader election algorithm takes no more than LN bits, where L ≃ 2.441716 and N denotes the size of the ring. We give a precise asymptotic analysis of the average number of rounds M (n) required by the algorithm, proving for example that M (∞) := lim n→∞ M (n) = 2.441715879. . ., where n is the number of starting candidates in the election. Accurate asymptotic expressions of the second moment M (2) (n) of the discrete random variable at hand, its probability distribution, and the generalization to all moments are given. Corresponding asymptotic expansions (n → ∞) are provided for sufficiently large j, where j counts the number of rounds. Our numerical results show that all computations perfectly fit the observed values. Finally, we investigate the generalization to probability t/n, where t is a non negative real parameter. The real function M (∞, t) := lim n→∞ M (n, t) is shown to admit one unique minimum M (∞, t *) on the real segment (0, 2). Furthermore, the variations of M (∞, t) on the whole real line are also studied in detail.

2010

study the problem of distributed leader election in an asynchronous complete network, in presence of faults that occurred prior to the execution of the election algorithm. Failures of this type are encountered, for example, during a recovery from a crash in the network. For a network with n processors, k of which start the algorithm and at most t of which might he faulty, we present an algorithm that uses at most O(n log k + n + kt) messages. We prove that this algorithm is optimal. We also present an optimal algorithm for the case where the identities of the neighbors are known. It is interesting to note that the order of the message complexity of a t-resilient algorithm is not always higher than that of a nonresilient one. The &resilient algorithm is a systematic modification of an existing algorithm for a faultfree network. Index Terms-Complete networks, distributed algorithms, fault-tolerance, leader election, message complexity. I.

We present an efficient randomized algorithm for leader election in large-scale distributed systems. The proposed algorithm is optimal in message complexity (O(n) for a set of n total processes), has round complexity logarithmic in the number of processes in the system, and provides high probabilistic guarantees on the election of a unique leader. The algorithm relies on a balls and bins abstraction and works in two phases. The main novelty of the work is in the first phase where the number of contending processes is reduced in a controlled manner. Probabilistic quorums are used to determine a winner in the second phase. We discuss, in detail, the synchronous version of the algorithm, provide extensions to an asynchronous version and examine the impact of failures.

2020

This paper presents a randomized self-stabilizing algorithm that elects a leader $r$ in a general $n$-node undirected graph and constructs a spanning tree $T$ rooted at $r$. The algorithm works under the synchronous message passing network model, assuming that the nodes know a linear upper bound on $n$ and that each edge has a unique ID known to both its endpoints (or, alternatively, assuming the $KT_{1}$ model). The highlight of this algorithm is its superior communication efficiency: It is guaranteed to send a total of $\tilde{O} (n)$ messages, each of constant size, till stabilization, while stabilizing in $\tilde{O} (n)$ rounds, in expectation and with high probability. After stabilization, the algorithm sends at most one constant size message per round while communicating only over the ($n - 1$) edges of $T$. In all these aspects, the communication overhead of the new algorithm is far smaller than that of the existing (mostly deterministic) self-stabilizing leader election algo...