基于节点复合特性的端-边协同网络生成算法

doi:10.12305/j.issn.1001-506X.2023.08.34

Abstract

Abstract:

For the difficult problem of large data processing volume and strict transmission time requirement of intelligent transportation system, an end-edge collaborative system with collaborative operation of device end and edge nodes is constructed by defining the collaborative system as a complex network model. A collaborative network generation algorithm based on network node composite characteristics is proposed to achieve multi-layer complex network's sconstruction. Compared with the random geometry method, the combination of two characteristic parameters, node clustering coefficient and the betweenness centrality, to generate the collaborative network generation algorithm can describe the node characteristics more comprehensively, reflect the node importance, and improve the problem of incomplete description of node information in the existing multilayer complex network models. Finally, use four complex network models to build multi-layer network model to verify the proposed algorithm. Taking the shortest route value between nodes as evaluation indicators, the proposed node composite characteristics can significantly reduce the shortest road value between nodes in the whole network, which could reduce transmission time and improve the transmission efficiency.

Key words: collaborative computing, complex network, network model, edge computing

CLC Number:

TP393

Bingxue ZHANG, Xisheng LI, Jia YOU, Weiren SONG. End-edge collaborative network generation algorithm based on node composite characteristics[J]. Systems Engineering and Electronics, 2023, 45(8): 2588-2596.

Figures/Tables 9

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References 35

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复杂网络模型	参数	取值
ER随机模型	节点总数/个	500
ER随机模型	连接概率	0.02
BA无标度模型	初始节点数/个	10
	最终节点数/个	500
	每次增加边数/条	2
WS小世界网络	节点总数/个	500
	每个节点邻居数/个	2
	随机重连概率	0.2
NW小世界网络	节点总数/个	500
	每个节点邻居数/个	2
	随机加边概率	0.01

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End-edge collaborative network generation algorithm based on node composite characteristics

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