{"title":"机会网络的随机模型","authors":"J. Visca, Matías Richart, J. Baliosian","doi":"10.1109/WCNCW.2019.8902544","DOIUrl":null,"url":null,"abstract":"Opportunistic Networks are networks in which data delivery is achieved taking advantage of fleeting and random encounters between mobile nodes. To study such networks, their models must take into account the stochastic nature of the processes involved. In this work we show how results from epidemiology can be used to study the behavior of opportunistic algorithms. In particular, we apply a Markov model for a logistic birth/death process to an epidemic networking deployment. The method is based on analyzing the expected lifetime of messages in the network, and allows to model networks were nodes have a limited buffer capacity.","PeriodicalId":121352,"journal":{"name":"2019 IEEE Wireless Communications and Networking Conference Workshop (WCNCW)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stochastic Models for Opportunistic Networks\",\"authors\":\"J. Visca, Matías Richart, J. Baliosian\",\"doi\":\"10.1109/WCNCW.2019.8902544\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Opportunistic Networks are networks in which data delivery is achieved taking advantage of fleeting and random encounters between mobile nodes. To study such networks, their models must take into account the stochastic nature of the processes involved. In this work we show how results from epidemiology can be used to study the behavior of opportunistic algorithms. In particular, we apply a Markov model for a logistic birth/death process to an epidemic networking deployment. The method is based on analyzing the expected lifetime of messages in the network, and allows to model networks were nodes have a limited buffer capacity.\",\"PeriodicalId\":121352,\"journal\":{\"name\":\"2019 IEEE Wireless Communications and Networking Conference Workshop (WCNCW)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Wireless Communications and Networking Conference Workshop (WCNCW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCNCW.2019.8902544\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Wireless Communications and Networking Conference Workshop (WCNCW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCNCW.2019.8902544","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Opportunistic Networks are networks in which data delivery is achieved taking advantage of fleeting and random encounters between mobile nodes. To study such networks, their models must take into account the stochastic nature of the processes involved. In this work we show how results from epidemiology can be used to study the behavior of opportunistic algorithms. In particular, we apply a Markov model for a logistic birth/death process to an epidemic networking deployment. The method is based on analyzing the expected lifetime of messages in the network, and allows to model networks were nodes have a limited buffer capacity.