论文标题
生成带有优先附件的随机bigraphs
Generating random bigraphs with preferential attachment
论文作者
论文摘要
Bigraph理论是一个相对年轻但正式严格的数学框架，一方面涵盖了Robin Milner先前在Process Calculi上的工作，另一方面为复杂系统（例如多代理系统）提供了通用的元模型。一个bigraph $ f = \ langle f^p，f^l \ rangle $是两个独立的图形结构的叠加，其中包括一个位置图$ f^p $（即森林）和链接图形$ f^l $（即超插图）（即，超级文字），共享相同的节点集，以表示相同的位置和交流，以表达与每个人独立于每个人独立于每个人独立于另一个。 在本文中，我们采取了一些准备步骤，用于算法，以生成具有优先附件特征W.R.T.的随机bigraphs。 $ f^p $和分类（拆卸）链接模式W.R.T. $ f^l $。我们采用参数，使一个人可以微调生成的Bigraph结构的特征。为了研究我们的算法模型的模式形成属性，我们根据不同配置下的人工创建的bigraphs分析了图理论的几个指标。 BigRaphs为移动和全局无处不在的计算过程提供了一种非常有用的和表现力的语义。到目前为止，该主题尚未在与Bigraph相关的科学文献中受到关注。但是，人工模型可能对在需要随机结构的无处不在系统中的现实世界应用进行仿真和评估特别有用。
The bigraph theory is a relatively young, yet formally rigorous, mathematical framework encompassing Robin Milner's previous work on process calculi, on the one hand, and provides a generic meta-model for complex systems such as multi-agent systems, on the other. A bigraph $F = \langle F^P, F^L\rangle$ is a superposition of two independent graph structures comprising a place graph $F^P$ (i.e., a forest) and a link graph $F^L$ (i.e., a hypergraph), sharing the same node set, to express locality and communication of processes independently from each other. In this paper, we take some preparatory steps towards an algorithm for generating random bigraphs with preferential attachment feature w.r.t. $F^P$ and assortative (disassortative) linkage pattern w.r.t. $F^L$. We employ parameters allowing one to fine-tune the characteristics of the generated bigraph structures. To study the pattern formation properties of our algorithmic model, we analyze several metrics from graph theory based on artificially created bigraphs under different configurations. Bigraphs provide a quite useful and expressive semantic for process calculi for mobile and global ubiquitous computing. So far, this subject has not received attention in the bigraph-related scientific literature. However, artificial models may be particularly useful for simulation and evaluation of real-world applications in ubiquitous systems necessitating random structures.
