{"title":"A New Cascading Model on Scale-Free Network with Tunable Parameter","authors":"Jianwei Wang, Lili Rong, L. Zhang","doi":"10.1109/ICINIS.2008.8","DOIUrl":null,"url":null,"abstract":"In this paper, we examine the cascading failure on BA networks with scale-free property based on a load redistribution rule. Assuming that the robustness is quantified by the critical threshold Tc, at which a phase transition occurs from normal state to collapse, we find the strongest robustness against cascading failures in the case of alpha =1, which is a tunable parameter in our model. We further discuss the correlations between the average degree <k> of BA network and Tc, and draw the conclusion that Tc has a negative correlation with the average degree <k>, i.e., the bigger the value of <k>, the smaller the critical threshold Tc. These results may be very helpful for real-life networks to avoid cascading-failure-induced disasters.","PeriodicalId":185739,"journal":{"name":"2008 First International Conference on Intelligent Networks and Intelligent Systems","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 First International Conference on Intelligent Networks and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINIS.2008.8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, we examine the cascading failure on BA networks with scale-free property based on a load redistribution rule. Assuming that the robustness is quantified by the critical threshold Tc, at which a phase transition occurs from normal state to collapse, we find the strongest robustness against cascading failures in the case of alpha =1, which is a tunable parameter in our model. We further discuss the correlations between the average degree of BA network and Tc, and draw the conclusion that Tc has a negative correlation with the average degree , i.e., the bigger the value of , the smaller the critical threshold Tc. These results may be very helpful for real-life networks to avoid cascading-failure-induced disasters.