Network Size Estimation in Small-World Networks Under Byzantine Faults

Soumyottam Chatterjee, Gopal Pandurangan, Peter Robinson
{"title":"Network Size Estimation in Small-World Networks Under Byzantine Faults","authors":"Soumyottam Chatterjee, Gopal Pandurangan, Peter Robinson","doi":"10.1109/IPDPS.2019.00094","DOIUrl":null,"url":null,"abstract":"We study the fundamental problem of counting the number of nodes in a sparse network (of unknown size) under the presence of a large number of Byzantine nodes. We assume the full information model where the Byzantine nodes have complete knowledge about the entire state of the network at every round (including random choices made by all the nodes), have unbounded computational power, and can deviate arbitrarily from the protocol. Essentially all known algorithms for fundamental Byzantine problems (e.g., agreement, leader election, sampling) studied in the literature assume the knowledge (or at least an estimate) of the size of the network. It is non-trivial to design algorithms for Byzantine problems that work without knowledge of the network size, especially in bounded-degree (expander) networks where the local views of all nodes are (essentially) the same and limited, and Byzantine nodes can quite easily fake the presence/absence of non-existing nodes. To design truly local algorithms that do not rely on any global knowledge (including network size), estimating the size of the network under Byzantine nodes is an important first step. Our main contribution is a randomized distributed algorithm that estimates the size of a network under the presence of a large number of Byzantine nodes. In particular, our algorithm estimates the size of a sparse, \"small-world\", expander network with up to O(n^1-Δ) Byzantine nodes, where n is the (unknown) network size and Δ > 0 can be be any arbitrarily small (but fixed) constant. Our algorithm outputs a (fixed) constant factor estimate of log(n) with high probability; the correct estimate of the network size will be known to a large fraction (1 - ε)-fraction, for any fixed positive constant ε) of the honest nodes. Our algorithm is fully distributed, lightweight, and simple to implement, runs in O(log^3 n) rounds, and requires nodes to send and receive messages of only small-sized messages per round; any node's local computation cost per round is also small.","PeriodicalId":403406,"journal":{"name":"2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPS.2019.00094","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

We study the fundamental problem of counting the number of nodes in a sparse network (of unknown size) under the presence of a large number of Byzantine nodes. We assume the full information model where the Byzantine nodes have complete knowledge about the entire state of the network at every round (including random choices made by all the nodes), have unbounded computational power, and can deviate arbitrarily from the protocol. Essentially all known algorithms for fundamental Byzantine problems (e.g., agreement, leader election, sampling) studied in the literature assume the knowledge (or at least an estimate) of the size of the network. It is non-trivial to design algorithms for Byzantine problems that work without knowledge of the network size, especially in bounded-degree (expander) networks where the local views of all nodes are (essentially) the same and limited, and Byzantine nodes can quite easily fake the presence/absence of non-existing nodes. To design truly local algorithms that do not rely on any global knowledge (including network size), estimating the size of the network under Byzantine nodes is an important first step. Our main contribution is a randomized distributed algorithm that estimates the size of a network under the presence of a large number of Byzantine nodes. In particular, our algorithm estimates the size of a sparse, "small-world", expander network with up to O(n^1-Δ) Byzantine nodes, where n is the (unknown) network size and Δ > 0 can be be any arbitrarily small (but fixed) constant. Our algorithm outputs a (fixed) constant factor estimate of log(n) with high probability; the correct estimate of the network size will be known to a large fraction (1 - ε)-fraction, for any fixed positive constant ε) of the honest nodes. Our algorithm is fully distributed, lightweight, and simple to implement, runs in O(log^3 n) rounds, and requires nodes to send and receive messages of only small-sized messages per round; any node's local computation cost per round is also small.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
拜占庭故障下小世界网络的网络大小估计
我们研究了在存在大量拜占庭节点的情况下,计算一个(未知大小)稀疏网络中节点数量的基本问题。我们假设完全信息模型,其中拜占庭节点在每轮中都完全了解网络的整个状态(包括所有节点所做的随机选择),具有无限的计算能力,并且可以任意偏离协议。从本质上讲,文献中研究的所有已知的基本拜占庭问题(例如,协议,领导者选举,抽样)的算法都假设知道(或至少估计)网络的大小。在不知道网络大小的情况下,为拜占庭问题设计算法是非常重要的,特别是在有界度(扩展器)网络中,所有节点的局部视图(本质上)是相同的和有限的,拜占庭节点可以很容易地假装不存在节点的存在/不存在。为了设计不依赖任何全局知识(包括网络大小)的真正的局部算法,估算拜占庭节点下的网络大小是重要的第一步。我们的主要贡献是一种随机分布算法,它可以在大量拜占庭节点存在的情况下估计网络的大小。特别是,我们的算法估计一个稀疏的,“小世界”的扩展网络的大小,该网络最多有O(n^1-Δ)个拜占庭节点,其中n是(未知的)网络大小,Δ > 0可以是任意小的(但固定的)常数。我们的算法以高概率输出log(n)的(固定)常数因子估计;对于诚实节点的很大一部分(1 - ε)(对于任何固定的正常数ε),网络大小的正确估计将是已知的。我们的算法是完全分布式的,轻量级的,易于实现的,在O(log^ 3n)轮中运行,并且要求节点每轮只发送和接收小消息;每轮任何节点的本地计算成本也很小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Distributed Weighted All Pairs Shortest Paths Through Pipelining SAFIRE: Scalable and Accurate Fault Injection for Parallel Multithreaded Applications Architecting Racetrack Memory Preshift through Pattern-Based Prediction Mechanisms Z-Dedup:A Case for Deduplicating Compressed Contents in Cloud Dual Pattern Compression Using Data-Preprocessing for Large-Scale GPU Architectures
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1