具有优先连接的随机偶图的生成
Generating random bigraphs with preferential attachment
摘要：
双图理论是一个相对年轻，但形式上严格的数学框架，一方面包含了罗宾·米尔纳以前在过程演算方面的工作，另一方面为复杂系统（如多智能体系统）提供了一个通用的元模型。偶图$F = \langle F^P, F^L\rangle$是包括位置图$F^P$（即，森林）和链接图$F^L$（即，超图），共享相同的节点集，以彼此独立地表示进程的局部性和通信。在本文中，我们采取了一些准备步骤，对算法产生的随机偶图的优先附件功能w.r.t. $F^P$和互作（不互作）连锁模式w.r.t. $F^L$。我们采用的参数，允许一个微调所生成的偶图结构的特性。为了研究我们的算法模型的模式形成特性，我们分析了几个指标，从图论的基础上人工创建的双图在不同的配置。双图为移动和全球普适计算的进程演算提供了一个非常有用和富有表现力的语义。到目前为止，这个问题还没有得到关注的bigraph相关的科学文献。然而，人工模型可能是特别有用的模拟和评估的现实世界中的应用程序在无处不在的系统需要随机结构。
英文摘要：
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.
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