Maximizing Algebraic Connectivity in the Space of Graphs With a Fixed Number of Vertices and Edges

被引:38
|
作者
Ogiwara, Kohnosuke [1 ]
Fukami, Tatsuya [1 ]
Takahashi, Norikazu [2 ]
机构
[1] Kyushu Univ, Grad Sch Informat Sci & Elect Engn, Fukuoka 8190395, Japan
[2] Okayama Univ, Grad Sch Nat Sci & Technol, Okayama 7008530, Japan
来源
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS | 2017年 / 4卷 / 02期
关键词
Algebraic connectivity; consensus algorithm; convergence rate; Laplacian matrix; multiagent network; MULTIAGENT SYSTEMS; TOPOLOGY DESIGN; CONSENSUS; TRANSPORTATION; NETWORK; AGENTS; COORDINATION; MAXIMIZATION; ALGORITHMS;
D O I
10.1109/TCNS.2015.2503561
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The second smallest eigenvalue of the Laplacian matrix, also known as the algebraic connectivity, characterizes the performance of some dynamic processes on networks, such as consensus in multiagent networks, synchronization of coupled oscillators, random walks on graphs, and so on. In a multiagent network, for example, the larger the algebraic connectivity of the graph representing interactions between agents is, the faster the convergence speed of a representative consensus algorithm is. This paper tackles the problem of finding graphs that maximize or locally maximize the algebraic connectivity in the space of graphs with a fixed number of vertices and edges. It is shown that some well-known classes of graphs such as star graphs, cycle graphs, complete bipartite graphs, and circulant graphs are algebraic connectivity maximizers or local maximizers under certain conditions.
引用
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页码:359 / 368
页数:10
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