{"title":"T 型间隔动态网络中的次线性算法","authors":"Irvan Jahja, Haifeng Yu","doi":"10.1007/s00453-024-01250-3","DOIUrl":null,"url":null,"abstract":"<div><p>We consider standard <i>T</i>-<i>interval dynamic networks</i>, under the synchronous timing model and the broadcast CONGEST model. In a <i>T</i>-<i>interval dynamic network</i>, the set of nodes is always fixed and there are no node failures. The edges in the network are always undirected, but the set of edges in the topology may change arbitrarily from round to round, as determined by some <i>adversary</i> and subject to the following constraint: For every <i>T</i> consecutive rounds, the topologies in those rounds must contain a common connected spanning subgraph. Let <span>\\(H_r\\)</span> to be the maximum (in terms of number of edges) such subgraph for round <i>r</i> through <span>\\(r+T-1\\)</span>. We define the <i>backbone diameter</i> <i>d</i> of a <i>T</i>-interval dynamic network to be the maximum diameter of all such <span>\\(H_r\\)</span>’s, for <span>\\(r\\ge 1\\)</span>. We use <i>n</i> to denote the number of nodes in the network. Within such a context, we consider a range of fundamental distributed computing problems including <span>Count</span>/<span>Max</span>/<span>Median</span>/<span>Sum</span>/<span>LeaderElect</span>/<span>Consensus</span>/<span>ConfirmedFlood</span>. Existing algorithms for these problems all have time complexity of <span>\\(\\Omega (n)\\)</span> rounds, even for <span>\\(T=\\infty \\)</span> and even when <i>d</i> is as small as <i>O</i>(1). This paper presents a novel approach/framework, based on the idea of <i>massively parallel aggregation</i>. Following this approach, we develop a novel deterministic <span>Count</span> algorithm with <span>\\(O(d^3 \\log ^2 n)\\)</span> complexity, for <i>T</i>-interval dynamic networks with <span>\\(T \\ge c\\cdot d^2 \\log ^2n\\)</span>. Here <i>c</i> is a (sufficiently large) constant independent of <i>d</i>, <i>n</i>, and <i>T</i>. To our knowledge, our algorithm is the very first such algorithm whose complexity does not contain a <span>\\(\\Theta (n)\\)</span> term. This paper further develops novel algorithms for solving <span>Max</span>/<span>Median</span>/<span>Sum</span>/<span>LeaderElect</span>/<span>Consensus</span>/<span>ConfirmedFlood</span>, while incurring <span>\\(O(d^3 \\text{ polylog }(n))\\)</span> complexity. Again, for all these problems, our algorithms are the first ones whose time complexity does not contain a <span>\\(\\Theta (n)\\)</span> term.</p></div>","PeriodicalId":50824,"journal":{"name":"Algorithmica","volume":"86 9","pages":"2959 - 2996"},"PeriodicalIF":0.9000,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sublinear Algorithms in T-Interval Dynamic Networks\",\"authors\":\"Irvan Jahja, Haifeng Yu\",\"doi\":\"10.1007/s00453-024-01250-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We consider standard <i>T</i>-<i>interval dynamic networks</i>, under the synchronous timing model and the broadcast CONGEST model. In a <i>T</i>-<i>interval dynamic network</i>, the set of nodes is always fixed and there are no node failures. The edges in the network are always undirected, but the set of edges in the topology may change arbitrarily from round to round, as determined by some <i>adversary</i> and subject to the following constraint: For every <i>T</i> consecutive rounds, the topologies in those rounds must contain a common connected spanning subgraph. Let <span>\\\\(H_r\\\\)</span> to be the maximum (in terms of number of edges) such subgraph for round <i>r</i> through <span>\\\\(r+T-1\\\\)</span>. We define the <i>backbone diameter</i> <i>d</i> of a <i>T</i>-interval dynamic network to be the maximum diameter of all such <span>\\\\(H_r\\\\)</span>’s, for <span>\\\\(r\\\\ge 1\\\\)</span>. We use <i>n</i> to denote the number of nodes in the network. Within such a context, we consider a range of fundamental distributed computing problems including <span>Count</span>/<span>Max</span>/<span>Median</span>/<span>Sum</span>/<span>LeaderElect</span>/<span>Consensus</span>/<span>ConfirmedFlood</span>. Existing algorithms for these problems all have time complexity of <span>\\\\(\\\\Omega (n)\\\\)</span> rounds, even for <span>\\\\(T=\\\\infty \\\\)</span> and even when <i>d</i> is as small as <i>O</i>(1). This paper presents a novel approach/framework, based on the idea of <i>massively parallel aggregation</i>. Following this approach, we develop a novel deterministic <span>Count</span> algorithm with <span>\\\\(O(d^3 \\\\log ^2 n)\\\\)</span> complexity, for <i>T</i>-interval dynamic networks with <span>\\\\(T \\\\ge c\\\\cdot d^2 \\\\log ^2n\\\\)</span>. Here <i>c</i> is a (sufficiently large) constant independent of <i>d</i>, <i>n</i>, and <i>T</i>. To our knowledge, our algorithm is the very first such algorithm whose complexity does not contain a <span>\\\\(\\\\Theta (n)\\\\)</span> term. This paper further develops novel algorithms for solving <span>Max</span>/<span>Median</span>/<span>Sum</span>/<span>LeaderElect</span>/<span>Consensus</span>/<span>ConfirmedFlood</span>, while incurring <span>\\\\(O(d^3 \\\\text{ polylog }(n))\\\\)</span> complexity. 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引用次数: 0
摘要
我们考虑的是同步定时模型和广播 CONGEST 模型下的标准 T 间隔动态网络。在 T 间隔动态网络中,节点集总是固定的,不存在节点故障。网络中的边总是无向的,但拓扑结构中的边集可以在各轮之间任意变化,由某个对手决定,并受到以下约束:每连续进行 T 轮,这些轮中的拓扑图必须包含一个共同的连通跨越子图。让 \(H_r\)成为第 r 轮通过 \(r+T-1\)的最大子图(以边的数量计算)。我们定义一个 T 期动态网络的主干直径 d 是所有这样的 \(H_r\) 的最大直径,对于 \(r\ge 1\) 来说。我们用 n 表示网络中的节点数。在这样的背景下,我们考虑了一系列基本的分布式计算问题,包括 Count/Max/Median/Sum/LeaderElect/Consensus/ConfirmedFlood 等。这些问题的现有算法的时间复杂度都是\(\Omega (n)\)轮,即使是\(T=\infty \),甚至当d小到O(1)时也是如此。本文提出了一种基于大规模并行聚合思想的新方法/框架。按照这种方法,我们开发了一种复杂度为(O(d^3 \log ^2 n))的新型确定性计数算法,适用于具有(T \ge c\cdot d^2 \log ^2n\ )的 T 期动态网络。据我们所知,我们的算法是第一个复杂度不包含(\Theta (n)\)项的算法。本文进一步开发了解决 Max/Median/Sum/LeaderElect/Consensus/ConfirmedFlood 问题的新算法,同时产生了 \(O(d^3 \text{ polylog }(n))\) 复杂性。同样,对于所有这些问题,我们的算法是第一个时间复杂度不包含一个(θ (n))项的算法。
Sublinear Algorithms in T-Interval Dynamic Networks
We consider standard T-interval dynamic networks, under the synchronous timing model and the broadcast CONGEST model. In a T-interval dynamic network, the set of nodes is always fixed and there are no node failures. The edges in the network are always undirected, but the set of edges in the topology may change arbitrarily from round to round, as determined by some adversary and subject to the following constraint: For every T consecutive rounds, the topologies in those rounds must contain a common connected spanning subgraph. Let \(H_r\) to be the maximum (in terms of number of edges) such subgraph for round r through \(r+T-1\). We define the backbone diameterd of a T-interval dynamic network to be the maximum diameter of all such \(H_r\)’s, for \(r\ge 1\). We use n to denote the number of nodes in the network. Within such a context, we consider a range of fundamental distributed computing problems including Count/Max/Median/Sum/LeaderElect/Consensus/ConfirmedFlood. Existing algorithms for these problems all have time complexity of \(\Omega (n)\) rounds, even for \(T=\infty \) and even when d is as small as O(1). This paper presents a novel approach/framework, based on the idea of massively parallel aggregation. Following this approach, we develop a novel deterministic Count algorithm with \(O(d^3 \log ^2 n)\) complexity, for T-interval dynamic networks with \(T \ge c\cdot d^2 \log ^2n\). Here c is a (sufficiently large) constant independent of d, n, and T. To our knowledge, our algorithm is the very first such algorithm whose complexity does not contain a \(\Theta (n)\) term. This paper further develops novel algorithms for solving Max/Median/Sum/LeaderElect/Consensus/ConfirmedFlood, while incurring \(O(d^3 \text{ polylog }(n))\) complexity. Again, for all these problems, our algorithms are the first ones whose time complexity does not contain a \(\Theta (n)\) term.
期刊介绍:
Algorithmica is an international journal which publishes theoretical papers on algorithms that address problems arising in practical areas, and experimental papers of general appeal for practical importance or techniques. The development of algorithms is an integral part of computer science. The increasing complexity and scope of computer applications makes the design of efficient algorithms essential.
Algorithmica covers algorithms in applied areas such as: VLSI, distributed computing, parallel processing, automated design, robotics, graphics, data base design, software tools, as well as algorithms in fundamental areas such as sorting, searching, data structures, computational geometry, and linear programming.
In addition, the journal features two special sections: Application Experience, presenting findings obtained from applications of theoretical results to practical situations, and Problems, offering short papers presenting problems on selected topics of computer science.