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P2 Equational Reasonings in Wireless Network Gossip Protocols

无线网络 Gossip 协议中的等式推理
LMCS vol.Volume 14, Issue 32018匹配度 1/10 · 该论文研究无线传感器网络中 gossip 协议的概率时间进程演算与模拟理论,属于形式语义和并发理论范畴,不涉及机器学习/Agent/LLM、静态分析、浮点程序分析或贝叶斯程序分析,与用户研究画像的核心方向基本无关。引用 4 inbox
Ruggero Lanotte, Massimo Merro, Simone Tini
crossref: 2026-09-10

AI 速览

一句话:提出无线传感器网络概率时间进程演算的模拟理论,并以代数定律组合式估计 gossip 协议性能。

Gossip 协议是大规模网络中鲁棒且高效的信息传播方法。本文针对无线传感器网络,提出一个简单的概率时间进程演算,用于表达 gossip 协议的形式化概率模型,并给出组合式分析技术。作者为该演算配备模拟理论,以在给定容差内比较行为相似的概率协议;该理论是弱互模拟度量的非对称变体,适合处理系统之间并非近似等价的协议。利用该理论研究并证明了若干代数定律,这些定律能有效估计存在或不存在通信冲突的 gossip 网络以及随机 gossip 网络的性能。

问题
如何组合式地分析无线传感器网络中 gossip 协议的概率模型,并在一定容差内比较协议行为。
方法
提出概率时间进程演算,并为其定义作为弱互模拟度量非对称变体的模拟理论,进而证明代数定律。
评估
用所得代数定律估计有无通信冲突的 gossip 网络及随机 gossip 网络的性能。
原文摘要(Abstract)

Gossip protocols have been proposed as a robust and efficient method for disseminating information throughout large-scale networks. In this paper, we propose a compositional analysis technique to study formal probabilistic models of gossip protocols expressed in a simple probabilistic timed process calculus for wireless sensor networks. We equip the calculus with a simulation theory to compare probabilistic protocols that have similar behaviour up to a certain tolerance. The theory is used to prove a number of algebraic laws which revealed to be very effective to estimate the performances of gossip networks, with and without communication collisions, and randomised gossip networks. Our simulation theory is an asymmetric variant of the weak bisimulation metric that maintains most of the properties of the original definition. However, our asymmetric version is particularly suitable to reason on protocols in which the systems under consideration are not approximately equivalent, as in the case of gossip protocols.

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BibTeX
@article{paperbot371,
  title = {Equational Reasonings in Wireless Network Gossip Protocols},
  author = {Ruggero Lanotte and Massimo Merro and Simone Tini},
  journal = {Logical Methods in Computer Science},
  volume = {Volume 14, Issue 3},
  year = {2018},
  doi = {10.23638/lmcs-14(3:24)2018}
}