{"title":"面向服务的网格环境的点对点元调度器","authors":"K. Dörnemann, Jörg Prenzer, Bernd Freisleben","doi":"10.4108/GRIDNETS.2007.2164","DOIUrl":null,"url":null,"abstract":"Meta-scheduling in a Grid is aimed at enabling the efficient sharing of computing resources managed by different local schedulers within a single organization or scattered across several administrative domains. Since current Grid metaschedulers operate in a centralized fashion and thus are single points of failure, we present a distributed meta-scheduler for a service-oriented Grid environment based on peer-to-peer (P2P) networking techniques and ant colony optimization algorithms adapted to a P2P network. In the proposed approach, the meta-scheduling process provides automatic load balancing, is completely decentralized, fault tolerant, scalable, and does not require complex administration. Experimental results demonstrate that scheduling decisions are made quickly and lead to a good balance of the computational load.","PeriodicalId":380761,"journal":{"name":"Networks for Grid Applications","volume":"07 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"A peer-to-peer meta-scheduler for service-oriented grid environments\",\"authors\":\"K. Dörnemann, Jörg Prenzer, Bernd Freisleben\",\"doi\":\"10.4108/GRIDNETS.2007.2164\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Meta-scheduling in a Grid is aimed at enabling the efficient sharing of computing resources managed by different local schedulers within a single organization or scattered across several administrative domains. Since current Grid metaschedulers operate in a centralized fashion and thus are single points of failure, we present a distributed meta-scheduler for a service-oriented Grid environment based on peer-to-peer (P2P) networking techniques and ant colony optimization algorithms adapted to a P2P network. In the proposed approach, the meta-scheduling process provides automatic load balancing, is completely decentralized, fault tolerant, scalable, and does not require complex administration. Experimental results demonstrate that scheduling decisions are made quickly and lead to a good balance of the computational load.\",\"PeriodicalId\":380761,\"journal\":{\"name\":\"Networks for Grid Applications\",\"volume\":\"07 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Networks for Grid Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4108/GRIDNETS.2007.2164\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Networks for Grid Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/GRIDNETS.2007.2164","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A peer-to-peer meta-scheduler for service-oriented grid environments
Meta-scheduling in a Grid is aimed at enabling the efficient sharing of computing resources managed by different local schedulers within a single organization or scattered across several administrative domains. Since current Grid metaschedulers operate in a centralized fashion and thus are single points of failure, we present a distributed meta-scheduler for a service-oriented Grid environment based on peer-to-peer (P2P) networking techniques and ant colony optimization algorithms adapted to a P2P network. In the proposed approach, the meta-scheduling process provides automatic load balancing, is completely decentralized, fault tolerant, scalable, and does not require complex administration. Experimental results demonstrate that scheduling decisions are made quickly and lead to a good balance of the computational load.