{"title":"共享ATM缓冲区的神经网络控制","authors":"I. Reljin, B. Reljin","doi":"10.1109/NEUREL.2002.1057978","DOIUrl":null,"url":null,"abstract":"Assuming the shared buffer in ATM node with bursty input traffic, we have derived a new competitive neural network algorithm for buffer management. The algorithm is an extended version of the previous one, based on input prebuffers solution. The cell loss rate obtained is considerably lower comparing to the round-robin control in such a case. The interarrival times of output streams are considered by fractal/multifractal analysis, as well.","PeriodicalId":347066,"journal":{"name":"6th Seminar on Neural Network Applications in Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2002-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Neural network control of shared ATM buffer\",\"authors\":\"I. Reljin, B. Reljin\",\"doi\":\"10.1109/NEUREL.2002.1057978\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Assuming the shared buffer in ATM node with bursty input traffic, we have derived a new competitive neural network algorithm for buffer management. The algorithm is an extended version of the previous one, based on input prebuffers solution. The cell loss rate obtained is considerably lower comparing to the round-robin control in such a case. The interarrival times of output streams are considered by fractal/multifractal analysis, as well.\",\"PeriodicalId\":347066,\"journal\":{\"name\":\"6th Seminar on Neural Network Applications in Electrical Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"6th Seminar on Neural Network Applications in Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NEUREL.2002.1057978\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"6th Seminar on Neural Network Applications in Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NEUREL.2002.1057978","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Assuming the shared buffer in ATM node with bursty input traffic, we have derived a new competitive neural network algorithm for buffer management. The algorithm is an extended version of the previous one, based on input prebuffers solution. The cell loss rate obtained is considerably lower comparing to the round-robin control in such a case. The interarrival times of output streams are considered by fractal/multifractal analysis, as well.
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