Compact Deterministic Self-Stabilizing Leader Election: The Exponential Advantage of Being Talkative

This paper focuses on compact deterministic self-stabilizing solutions for the leader election problem. When the protocol is required to be \emph{silent} (i.e., when communication content remains fixed from some point in time during any execution), there exists a lower bound of Omega(\log n) bits of memory per node participating to the leader election (where n denotes the number of nodes in the system). This lower bound holds even in rings. We present a new deterministic (non-silent) 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, the communication model fits with the model used by existing compilers for real networks. Second, the size of the ring (or any upper bound on this size) needs not to be known by any node. Third, the node identifiers can be of various sizes. Finally, no synchrony assumption, besides a weakly fair scheduler, is assumed. Therefore, our result shows that, perhaps surprisingly, trading silence for exponential improvement in term of memory space does not come at a high cost regarding stabilization time or minimal assumptions

Evolution, appearance, and occupational success

Visual characteristics, including facial appearance, are thought to play an important role in a variety of judgments and decisions that have real occupational outcomes in many settings. Indeed, there is growing evidence suggesting that appearance influences hiring decisions and even election results. For example, attractive individuals are more likely to be hired, taller men earn more, and the facial appearance of candidates has been linked to real election outcomes. In this article, we review evidence linking physical appearance to occupational success and evaluate the hypothesis that appearance based biases are consistent with predictions based on evolutionary theories of coalition formation and leadership choice. We discuss why appearance based effects are so pervasive, addressing ideas about a "kernel of truth" in attributions and about coalitional psychology. We additionally highlight that appearance may be differently related to success at work according to the types of job or task involved. For example, leaders may be chosen because the characteristics they possess are seen as best suited to lead in particular situations. During a time of war, a dominant-appearing leader may inspire confidence and intimidate enemies while during peace-time, when negotiation and diplomacy are needed, interpersonal skills may outweigh the value of a dominant leader. In line with these ideas, masculine-faced leaders are favored in war-time scenarios while feminine-faced leaders are favored in peace-time scenarios. We suggest that such environment or task specific competencies may be prevalent during selection processes, whereby individuals whose appearance best matches perceived task competences are most likely selected, and propose the general term "task-congruent selection" to describe these effects. Overall, our review highlights how potentially adaptive biases could influence choices in the work place. With respect to certain biases, understanding their origin and current prevalence is important in order to potentially reduce discrimination in the work place

Optimal strategies for selecting coordinators

We study optimal election sequences for repeatedly selecting a (very) small group of leaders among a set of participants (players) with publicly known unique ids. In every time slot, every player has to select exactly one player that it considers to be the current leader, oblivious to the selection of the other players, but with the overarching goal of maximizing a given parameterized global (“social”) payoff function in the limit. We consider a quite generic model, where the local payoff achieved by a given player depends, weighted by some arbitrary but fixed real parameter, on the number of different leaders chosen in a round, the number of players that choose the given player as the leader, and whether the chosen leader has changed w.r.t. the previous round or not. The social payoff can be the maximum, average or minimum local payoff of the players. Possible applications include quite diverse examples such as rotating coordinator-based distributed algorithms and long-haul formation flying of social birds. Depending on the weights and the particular social payoff, optimal sequences can be very different, from simple round-robin where all players chose the same leader alternatingly every time slot to very exotic patterns, where a small group of leaders (at most 2) is elected in every time slot. Moreover, we study the question if and when a single player would not benefit w.r.t. its local payoff when deviating from the given optimal sequence, i.e., when our optimal sequences are Nash equilibria in the restricted strategy space of oblivious strategies. As this is the case for many parameterizations of our model, our results reveal that no punishment is needed to make it rational for the players to optimize the social payoff

Robust Leader Election in a Fast-Changing World

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 Las Vegas 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 ad-hoc 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 omega(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.Comment: In Proceedings FOMC 2013, arXiv:1310.459