网络的距离边缘监测集

IF 0.4 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Gang Yang, Jiannan Zhou, Changxiang He, Yaping Mao
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引用次数: 0

摘要

重要的是能够监控网络,并在连接(边)失效时检测到这种故障。对于图 G 的顶点集 M 和边 e,让 P(M,e)成为具有 M 的顶点 x 和 V(G)的顶点 y,且 e 属于 x 和 y 之间所有最短路径的对 (x, y) 的集合。如果图 G 的每条边 e 都受到 M 的某个顶点的监控,即集合 P(M, e) 非空,那么图 G 的顶点集 M 就是距离-边监控集。Foucaud, Kao, Klasing, Miller 和 Ryan 最近提出了图 G 的距离边监控数,它被定义为 G 的距离边监控集的最小大小。在本文中,我们确定了基于网格的金字塔的距离边监控数的边界,以及 M(t)-graph 和 Sierpiński-type 图的距离边监控数的精确值。我们还比较了距离边监控集与 G 的平均度、边集大小和顶点集大小(其中 G 为 M(t)-graph 或 Sierpiński-type 图)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Distance-edge-monitoring sets of networks

Distance-edge-monitoring sets of networks

It is important to be able to monitor the network and detect this failure when a connection (an edge) fails. For a vertex set M and an edge e of the graph G, let P(Me) be the set of pairs (xy) with a vertex x of M and a vertex y of V(G) such that e belongs to all shortest paths between x and y. A vertex set M of the graph G is distance-edge-monitoring set if every edge e of G is monitored by some vertex of M, that is, the set P(Me) is nonempty. The distance-edge-monitoring number of a graph G, recently introduced by Foucaud, Kao, Klasing, Miller, and Ryan, is defined as the smallest size of distance-edge-monitoring sets of G. In this paper, we determine the bounds of the distance-edge-monitoring number of grid-based pyramids and the exact value of distance-edge-monitoring number for M(t)-graph and Sierpiński-type graphs. We also compare the distance-edge-monitoring set with average degree, the size of edge set and the size of vertex set of G, where G is M(t)-graph or Sierpiński-type graphs.

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来源期刊
Acta Informatica
Acta Informatica 工程技术-计算机:信息系统
CiteScore
2.40
自引率
16.70%
发文量
24
审稿时长
>12 weeks
期刊介绍: Acta Informatica provides international dissemination of articles on formal methods for the design and analysis of programs, computing systems and information structures, as well as related fields of Theoretical Computer Science such as Automata Theory, Logic in Computer Science, and Algorithmics. Topics of interest include: • semantics of programming languages • models and modeling languages for concurrent, distributed, reactive and mobile systems • models and modeling languages for timed, hybrid and probabilistic systems • specification, program analysis and verification • model checking and theorem proving • modal, temporal, first- and higher-order logics, and their variants • constraint logic, SAT/SMT-solving techniques • theoretical aspects of databases, semi-structured data and finite model theory • theoretical aspects of artificial intelligence, knowledge representation, description logic • automata theory, formal languages, term and graph rewriting • game-based models, synthesis • type theory, typed calculi • algebraic, coalgebraic and categorical methods • formal aspects of performance, dependability and reliability analysis • foundations of information and network security • parallel, distributed and randomized algorithms • design and analysis of algorithms • foundations of network and communication protocols.
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