Fast and succinct population protocols for Presburger arithmetic

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE Journal of Computer and System Sciences Pub Date : 2023-09-29 DOI:10.1016/j.jcss.2023.103481
Philipp Czerner, Roland Guttenberg, Martin Helfrich, Javier Esparza
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Abstract

In their 2006 seminal paper in Distributed Computing, Angluin et al. present a construction that, given any Presburger predicate, outputs a leaderless population protocol that decides the predicate. The protocol for a predicate of size m runs in O(mn2logn) expected number of interactions, which is almost optimal in n, the number of interacting agents. However, the number of states is exponential in m. Blondin et al. presented at STACS 2020 another construction that produces protocols with a polynomial number of states, but exponential expected number of interactions. We present a construction that produces protocols with O(m) states that run in expected O(m7n2) interactions, optimal in n, for all inputs of size Ω(m). For this, we introduce population computers, a generalization of population protocols, and show that our computers for Presburger predicates can be translated into fast and succinct population protocols.

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快速和简洁的人口协议的普雷斯伯格算法
Angluin等人在2006年发表在《分布式计算》(Distributed Computing)上的开创性论文中提出了一种构造,给定任何Presburger谓词,输出一个决定谓词的无领导人口协议。对于大小为m的谓词,协议在O(m·n2log (n))预期交互数下运行,这在n(交互代理的数量)下几乎是最优的。然而,m中的状态数是指数的。Blondin等人在STACS 2020上提出了另一种结构,该结构产生的协议具有多项式的状态数,但期望的相互作用数是指数的。我们提出了一种结构,该结构产生具有O(m)个状态的协议,这些状态在预期的O(m7·n2)相互作用中运行,在n中最优,对于大小为Ω(m)的所有输入。为此,我们引入了种群计算机,种群协议的一种推广,并表明我们的Presburger谓词计算机可以转换为快速简洁的种群协议。
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来源期刊
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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