Y. Murata, H. Takizawa, T. Inaba, Hiroaki Kobayashi
{"title":"大规模P2P系统的分布式协同负载平衡机制","authors":"Y. Murata, H. Takizawa, T. Inaba, Hiroaki Kobayashi","doi":"10.1109/SAINT-W.2006.2","DOIUrl":null,"url":null,"abstract":"This paper proposes a distributed and cooperative scheduling mechanism for dynamic load-balancing on a large-scale distributed computing environment. In the proposed mechanism, the scheduling processes are performed by independent distributed schedulers on individual computing resources. Decentralized mechanisms are more suitable for dynamic load-balancing of a large-scale distributed computing environment than centralized mechanisms in terms of scalability and fault tolerance. Experimental results show that the proposed scheduling mechanism has high scalability and efficiency, without any excessive concentration of processing even if the number of computing resources increases","PeriodicalId":297153,"journal":{"name":"International Symposium on Applications and the Internet Workshops (SAINTW'06)","volume":"119 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":"{\"title\":\"A distributed and cooperative load balancing mechanism for large-scale P2P systems\",\"authors\":\"Y. Murata, H. Takizawa, T. Inaba, Hiroaki Kobayashi\",\"doi\":\"10.1109/SAINT-W.2006.2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a distributed and cooperative scheduling mechanism for dynamic load-balancing on a large-scale distributed computing environment. In the proposed mechanism, the scheduling processes are performed by independent distributed schedulers on individual computing resources. Decentralized mechanisms are more suitable for dynamic load-balancing of a large-scale distributed computing environment than centralized mechanisms in terms of scalability and fault tolerance. Experimental results show that the proposed scheduling mechanism has high scalability and efficiency, without any excessive concentration of processing even if the number of computing resources increases\",\"PeriodicalId\":297153,\"journal\":{\"name\":\"International Symposium on Applications and the Internet Workshops (SAINTW'06)\",\"volume\":\"119 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-01-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"35\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Symposium on Applications and the Internet Workshops (SAINTW'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAINT-W.2006.2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Applications and the Internet Workshops (SAINTW'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAINT-W.2006.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A distributed and cooperative load balancing mechanism for large-scale P2P systems
This paper proposes a distributed and cooperative scheduling mechanism for dynamic load-balancing on a large-scale distributed computing environment. In the proposed mechanism, the scheduling processes are performed by independent distributed schedulers on individual computing resources. Decentralized mechanisms are more suitable for dynamic load-balancing of a large-scale distributed computing environment than centralized mechanisms in terms of scalability and fault tolerance. Experimental results show that the proposed scheduling mechanism has high scalability and efficiency, without any excessive concentration of processing even if the number of computing resources increases