{"title":"A Generic Learning Approach to Modelling Netflows from Historic Observations","authors":"Peter Chronz, F. Feldhaus, P. Kasprzak","doi":"10.1109/OCS.2012.36","DOIUrl":"https://doi.org/10.1109/OCS.2012.36","url":null,"abstract":"In this paper we present a generic learning algo- rithm that models the communication patterns between services. Current service landscapes especially in federated environments are characterized by a huge number of services and by a high de- gree of change. In this paper we present a method for quantifying the communication patterns between services in a autonomous fashion to allow predictions of future usage patterns in the service landscape for optimization and simulation. The proposed learning algorithm uses machine learning techniques and generates a probabilistic model based on observed network flow information. We perform the learning and evaluate the learning algorithm based on real world netflow data captured on a cloud testbed. The paper finally discusses potential applications of the proposed algorithm in a autonomous optimization framework for service management.","PeriodicalId":244833,"journal":{"name":"2012 7th Open Cirrus Summit","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127352533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}