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An effective reliability evaluation method for power communication network based on community structure

Citation

Li, Q and Cao, Z and Tanveer, M and Pandy, HM and Wang, C, An effective reliability evaluation method for power communication network based on community structure, IEEE Transactions on Industry Applications ISSN 0093-9994 (In Press) [Refereed Article]

Copyright Statement

Copyright 2019 IEEE

DOI: doi:10.1109/TIA.2019.2954272

Abstract

The reliability evaluation of the power communication network is beneficial for the improvement of the stable operation of the power system and the robustness of the power grid. However, the existing reliability evaluation models of the power communication network cannot meet the current situation of timeliness performance, due to rapidly increasing scale and complexity of information across varying services. In this study, we used the complex network theory to analyze the structure of the power communication network. Then we constructed the evaluation index of node (link) reliability of the power communication network based on community reliability. Compared with the traditional reliability indexes, our index not only considers the influence of the environment of the node (link) on the single structure of the power communication network, but also possess the reliability evaluation rate of the node (link), which have the opportunities for improving the performance of the reliability evaluation of the wide-area power communication network. To verify the rationality of the index, we developed random, low reliability and high-betweenness deliberate attacks to attack the designated node (link), and compared the network efficiency before and after the attack. Based on the simulation results, it can verify the rationality and superiority of our proposed evaluation index.

Item Details

Item Type:Refereed Article
Keywords:complex network, security, community structure, power communication network, reliability
Research Division:Information and Computing Sciences
Research Group:Artificial Intelligence and Image Processing
Research Field:Pattern Recognition and Data Mining
Objective Division:Defence
Objective Group:Defence
Objective Field:Intelligence
UTAS Author:Cao, Z (Mr Zehong Cao)
ID Code:135837
Year Published:In Press
Deposited By:Information and Communication Technology
Deposited On:2019-11-16
Last Modified:2019-12-12
Downloads:0

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