{"title":"网络演化模型的数值分析","authors":"I. Fazekas, Attila Perecsényi, B. Porvázsnyik","doi":"10.1109/COGINFOCOM.2017.8268236","DOIUrl":null,"url":null,"abstract":"In this paper we introduce a new network evolution model. The basic feature of the model is the cooperation (interaction) of N nodes. In our model every step m new nodes are born, where m is a discrete random variable with values 0,1, 2,…, N − 1. Then the m new nodes interact with (N − m) old vertices, so that they form a complete graph on N vertices. The old nodes can be chosen either uniformly or by using the preferential attachment rule. We analyze certain properties of the above mentioned model by computer simulations. Power-law degree and weight distributions and clustering coefficients are studied.","PeriodicalId":212559,"journal":{"name":"2017 8th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Numerical analysis of a network evolution model\",\"authors\":\"I. Fazekas, Attila Perecsényi, B. Porvázsnyik\",\"doi\":\"10.1109/COGINFOCOM.2017.8268236\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we introduce a new network evolution model. The basic feature of the model is the cooperation (interaction) of N nodes. In our model every step m new nodes are born, where m is a discrete random variable with values 0,1, 2,…, N − 1. Then the m new nodes interact with (N − m) old vertices, so that they form a complete graph on N vertices. The old nodes can be chosen either uniformly or by using the preferential attachment rule. We analyze certain properties of the above mentioned model by computer simulations. Power-law degree and weight distributions and clustering coefficients are studied.\",\"PeriodicalId\":212559,\"journal\":{\"name\":\"2017 8th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)\",\"volume\":\"55 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 8th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COGINFOCOM.2017.8268236\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 8th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COGINFOCOM.2017.8268236","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper we introduce a new network evolution model. The basic feature of the model is the cooperation (interaction) of N nodes. In our model every step m new nodes are born, where m is a discrete random variable with values 0,1, 2,…, N − 1. Then the m new nodes interact with (N − m) old vertices, so that they form a complete graph on N vertices. The old nodes can be chosen either uniformly or by using the preferential attachment rule. We analyze certain properties of the above mentioned model by computer simulations. Power-law degree and weight distributions and clustering coefficients are studied.