Building Graphs with Maximum Connectivity

M. Jafarpour, Mohammad Shekaramiz, A. Javan, A. Moeini
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Abstract

The increasing data volume and the algorithms complexity in recent years has made topics such as cloud computing extremely important. Meanwhile, improving the communication parameters in cloud computing has led to improvements such as the increase in efficiency, and the reduction of execution time and the energy consumption. The concept of communication can be treated as mathematical modeling with graphs, where the network requirements are evaluated with the graph parameters. Parameters such as connectivity, toughness, tenacity, and graph diameter are commonly used in cloud computing, social networks, networks security, etc. For example, connectivity is one of the major graph parameters that defines the extent of the graph's vulnerability. This parameter is evaluated in two vertex and edge modes. Creating graphs with a maximum vertex connectivity value was proposed by Harary and is referred to as Harary graphs. In this paper, we explore other graphs that have a different structure from Harary graphs and we make an attempt to improve other parameters such as graph diameter and toughness in the proposed graphs. In addition to cloud computing, the theoretical results of the proposed models are applicable in various fields such as social networks, network security, electronic circuit design, geography and urban design, bioinformatics and more.
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构建具有最大连通性的图
近年来,随着数据量和算法复杂度的不断增加,云计算等话题变得尤为重要。同时,云计算中通信参数的改进也带来了效率的提高、执行时间的缩短和能耗的降低等方面的改进。通信的概念可以看作是图形的数学建模,其中网络需求是用图形参数来评估的。连接性、韧性、韧性、图直径等参数在云计算、社交网络、网络安全等领域都很常用。例如,连通性是定义图的漏洞程度的主要图参数之一。该参数在两个顶点和边缘模式下计算。创建顶点连通性值最大的图是由Harary提出的,称为Harary图。在本文中,我们探索了与Harary图具有不同结构的其他图,并尝试改进所提出图中的其他参数,如图直径和韧性。除云计算外,所提出模型的理论结果可应用于社交网络、网络安全、电子电路设计、地理与城市设计、生物信息学等各个领域。
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