{"title":"异构计算系统的高效算法","authors":"S. Bansal, C. Hota","doi":"10.1109/ReTIS.2011.6146840","DOIUrl":null,"url":null,"abstract":"Distributed task scheduling in a heterogeneous computing environment is one of the most challenging problems. The optimally mapping of independent tasks onto heterogeneous distributed computing systems is known to be NP-complete. The most common objective function of a distributed task scheduling problem is to reduce the make span and increase the load balancing across the machines. In this paper, we introduce a new scheduling algorithm called, Efficient Algorithm on Heterogeneous Computing System (EAHCS) which balances the load well across the machines and reduces the make span time. In our evaluation study, a number of experiments with various simulation settings have been conducted. The results obtained using the proposed heuristic improves over the existing approaches.","PeriodicalId":137916,"journal":{"name":"2011 International Conference on Recent Trends in Information Systems","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Efficient Algorithm on heterogeneous computing system\",\"authors\":\"S. Bansal, C. Hota\",\"doi\":\"10.1109/ReTIS.2011.6146840\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Distributed task scheduling in a heterogeneous computing environment is one of the most challenging problems. The optimally mapping of independent tasks onto heterogeneous distributed computing systems is known to be NP-complete. The most common objective function of a distributed task scheduling problem is to reduce the make span and increase the load balancing across the machines. In this paper, we introduce a new scheduling algorithm called, Efficient Algorithm on Heterogeneous Computing System (EAHCS) which balances the load well across the machines and reduces the make span time. In our evaluation study, a number of experiments with various simulation settings have been conducted. The results obtained using the proposed heuristic improves over the existing approaches.\",\"PeriodicalId\":137916,\"journal\":{\"name\":\"2011 International Conference on Recent Trends in Information Systems\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Recent Trends in Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ReTIS.2011.6146840\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Recent Trends in Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ReTIS.2011.6146840","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient Algorithm on heterogeneous computing system
Distributed task scheduling in a heterogeneous computing environment is one of the most challenging problems. The optimally mapping of independent tasks onto heterogeneous distributed computing systems is known to be NP-complete. The most common objective function of a distributed task scheduling problem is to reduce the make span and increase the load balancing across the machines. In this paper, we introduce a new scheduling algorithm called, Efficient Algorithm on Heterogeneous Computing System (EAHCS) which balances the load well across the machines and reduces the make span time. In our evaluation study, a number of experiments with various simulation settings have been conducted. The results obtained using the proposed heuristic improves over the existing approaches.