This paper shows for the first time that distributed computing can be both reliable and efficient in an environment that is both highly dynamic and hostile. More specifically, we show how to maintain clusters of size O(log N ), each containing more than two thirds of honest nodes with high probability, within a system whose size can vary polynomially with respect to its initial size. Furthermore, the communication cost induced by each node arrival or departure is polylogarithmic with respect to N , the maximal size of the system. Our clustering can be achieved despite the presence of a Byzantine adversary controlling a fraction τ ≤ 1 3− of the nodes, for some fixed constant > 0, independent of N . So far, such a clustering could only be performed for systems whose size can vary constantly and it was not clear whether that was at all possible for polynomial variances.
is paper presents the first probabilistic Byzantine Agreement algorithm whose communication and time complexities are poly-logarithmic. So far, the most effective probabilistic Byzantine Agreement algorithm had communication complexityÕ n and time complexityÕ (1). Our algorithm is based on a novel, unbalanced, almost everywhere to everywhere Agreement protocol which is interesting in its own right.
Abstract.A wide range of applications in wireless sensor networks rely on the location information of the sensing nodes. However, traditional localization techniques are dependent on hardware that is sometimes unavailable (e.g. GPS), or on sophisticated virtual localization calculus which have a costly overhead.Instead of actually localizing nodes in the physical two-dimensional Euclidean space, we use directly the raw distance to a set of anchors to produce multi-dimensional coordinates. We prove that the image of the physical two-dimensional Euclidean space is a two-dimensional surface, and we show that it is possible to adapt geographic routing strategies on this surface, simply, efficiently and successfully.
Abstract-In this paper, we propose an efficient planarization algorithm and a routing algorithm dedicated to Unit Disk Graphs whose nodes are localized using the Virtual Raw Anchor Coordinate system (VRAC). Our first algorithm computes a planar 2-spanner under light constraints on the edge lengths and induces a total exchange of at most 6n node identifiers. Its total computational complexity is O(n∆), with ∆ the maximum degree of the communication graph. The second algorithm that we present is a simple and efficient algorithm to route messages in this planar graph that requires routing tables with only three entries. We support these theoretical results by simulations showing the robustness of our algorithms when the coordinates are inaccurate.
Abstract-We consider the problem of securely conducting a poll in synchronous dynamic networks equipped with a Public Key Infrastructure (PKI). Whereas previous distributed solutions had a communication cost of O(n 2 ) in an n nodes system, we present SPP (Secure and Private Polling), the first distributed polling protocol requiring only a communication complexity of O(n log 3 n), which we prove is near-optimal. Our protocol ensures perfect security against a computationally-bounded adversary, tolerates ( > > 0 (not depending on n), and outputs the exact value of the poll with high probability. SPP is composed of two sub-protocols, which we believe to be interesting on their own: SPP-Overlay maintains a structured overlay when nodes leave or join the network, and SPP-Computation conducts the actual poll. We validate the practicality of our approach through experimental evaluations and describe briefly two possible applications of SPP: (1) an optimal Byzantine Agreement protocol whose communication complexity is Θ(n log n) and (2) a protocol solving an open question of King and Saia in the context of aggregation functions, namely on the feasibility of performing multiparty secure aggregations with a communication complexity of o(n 2 ).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.