用图变换构造增量式拓扑控制算法的系统方法
A Systematic Approach to Constructing Incremental Topology Control Algorithms Using Graph Transformation
摘要：
通信网络是我们社会的支柱。拓扑控制算法优化这种通信网络的拓扑。由于通信网络的重要性，拓扑控制算法应该保证某些所需的一致性属性（例如，拓扑的连通性），同时实现期望的优化属性（例如，有界数目的邻居）。现实世界的拓扑是动态的（例如，因为节点在网络内加入、离开或移动），这要求拓扑控制算法以增量方式操作，即，基于最近引入的拓扑修改。可视化编程和规约语言是一种行之有效的手段，用于指定结构以及拓扑结构的一致性和优化特性。在本文中，我们提出了一种新的方法，基于一个可视化的图形转换和图形约束语言，开发增量拓扑控制算法，保证满足一组指定的一致性和优化约束。更具体地说，我们建模的拓扑控制算法和环境的可能的修改，使用图形转换规则，我们描述的一致性和优化特性，使用图形约束。在此基础上，我们应用并扩展了一个众所周知的建设性的方法来获得精细的图变换规则，保持这些图的约束。我们应用我们的方法来重新设计一个既定的拓扑控制算法，kTC，并评估它在网络仿真研究，以显示我们的方法的实用性
英文摘要：
Communication networks form the backbone of our society. Topology control algorithms optimize the topology of such communication networks. Due to the importance of communication networks, a topology control algorithm should guarantee certain required consistency properties (e.g., connectivity of the topology), while achieving desired optimization properties (e.g., a bounded number of neighbors). Real-world topologies are dynamic (e.g., because nodes join, leave, or move within the network), which requires topology control algorithms to operate in an incremental way, i.e., based on the recently introduced modifications of a topology. Visual programming and specification languages are a proven means for specifying the structure as well as consistency and optimization properties of topologies. In this paper, we present a novel methodology, based on a visual graph transformation and graph constraint language, for developing incremental topology control algorithms that are guaranteed to fulfill a set of specified consistency and optimization constraints. More specifically, we model the possible modifications of a topology control algorithm and the environment using graph transformation rules, and we describe consistency and optimization properties using graph constraints. On this basis, we apply and extend a well-known constructive approach to derive refined graph transformation rules that preserve these graph constraints. We apply our methodology to re-engineer an established topology control algorithm, kTC, and evaluate it in a network simulation study to show the practical applicability of our approach
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