{"title":"Cascading network failure based on local load distribution and non-linear relationship between initial load and capacity","authors":"Yi-Hua Ma, Dong-Li Zhang","doi":"10.1109/ICMLC.2012.6359479","DOIUrl":null,"url":null,"abstract":"Inspired by previous existing works, based on the local preferential redistribution rule of the load and the non-linear relation between load and capacity, we put forward a cascading model which is more practical and more suitable for real networks. We analyze the model theoretically and simulate it on BA scale-free network. In comparison with the strongest robustness against cascading failures of the linear load-capacity model in the case of α = 0.5 , we find that the robustness of the network can reach stronger in the case of δ ≠ 1, which is a tunable parameter controlling the strength of the capacity of node in our model. The results show that the model is effective. So it may be helpful to control cascading network failure and research on cascading failure deeply.","PeriodicalId":128006,"journal":{"name":"2012 International Conference on Machine Learning and Cybernetics","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2012.6359479","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Inspired by previous existing works, based on the local preferential redistribution rule of the load and the non-linear relation between load and capacity, we put forward a cascading model which is more practical and more suitable for real networks. We analyze the model theoretically and simulate it on BA scale-free network. In comparison with the strongest robustness against cascading failures of the linear load-capacity model in the case of α = 0.5 , we find that the robustness of the network can reach stronger in the case of δ ≠ 1, which is a tunable parameter controlling the strength of the capacity of node in our model. The results show that the model is effective. So it may be helpful to control cascading network failure and research on cascading failure deeply.