{"title":"关于规模经济对科学界影响的调查","authors":"S. Verma, R. Satao","doi":"10.1109/ICACEA.2015.7164784","DOIUrl":null,"url":null,"abstract":"Cloud computing is commonly characterized as a sort of computing that depends on offering computing resources instead of having neighborhood servers or individual gadgets to handle applications. The resource suppliers give adaptable resources to the client. In this paper, we propose to discover it out whether the little or medium scale scientific communities can utilize the economies of scale as a part of the cloud for its advantages. In this paper, we propose a Public Cloud model for leasing the adaptable resources from any open cloud supplier to the little or medium scale research associations. On the premise of this Public Cloud model, we are actualizing a novel strategy to handle the heterogeneous scientific workload on the cloud. The two average workloads are contemplated in this paper: High Throughput Computing (HTC) and Many Task Computing (MTC). Our workload taking care of the system can spare the aggregate resource utilization in both these workloads viably. We are proposing a novel scheduling technique, “Earlier Account Expire Prioritized with Round Robin (EAEP-RR) scheduling”, to handle the requests at cloud. At last, we can presume that our routines can advantage the scientific communities from the economies of scale in the cloud environment.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A survey on the impact of economies of scale on scientific communities\",\"authors\":\"S. Verma, R. Satao\",\"doi\":\"10.1109/ICACEA.2015.7164784\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cloud computing is commonly characterized as a sort of computing that depends on offering computing resources instead of having neighborhood servers or individual gadgets to handle applications. The resource suppliers give adaptable resources to the client. In this paper, we propose to discover it out whether the little or medium scale scientific communities can utilize the economies of scale as a part of the cloud for its advantages. In this paper, we propose a Public Cloud model for leasing the adaptable resources from any open cloud supplier to the little or medium scale research associations. On the premise of this Public Cloud model, we are actualizing a novel strategy to handle the heterogeneous scientific workload on the cloud. The two average workloads are contemplated in this paper: High Throughput Computing (HTC) and Many Task Computing (MTC). Our workload taking care of the system can spare the aggregate resource utilization in both these workloads viably. We are proposing a novel scheduling technique, “Earlier Account Expire Prioritized with Round Robin (EAEP-RR) scheduling”, to handle the requests at cloud. At last, we can presume that our routines can advantage the scientific communities from the economies of scale in the cloud environment.\",\"PeriodicalId\":202893,\"journal\":{\"name\":\"2015 International Conference on Advances in Computer Engineering and Applications\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Advances in Computer Engineering and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACEA.2015.7164784\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Advances in Computer Engineering and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACEA.2015.7164784","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A survey on the impact of economies of scale on scientific communities
Cloud computing is commonly characterized as a sort of computing that depends on offering computing resources instead of having neighborhood servers or individual gadgets to handle applications. The resource suppliers give adaptable resources to the client. In this paper, we propose to discover it out whether the little or medium scale scientific communities can utilize the economies of scale as a part of the cloud for its advantages. In this paper, we propose a Public Cloud model for leasing the adaptable resources from any open cloud supplier to the little or medium scale research associations. On the premise of this Public Cloud model, we are actualizing a novel strategy to handle the heterogeneous scientific workload on the cloud. The two average workloads are contemplated in this paper: High Throughput Computing (HTC) and Many Task Computing (MTC). Our workload taking care of the system can spare the aggregate resource utilization in both these workloads viably. We are proposing a novel scheduling technique, “Earlier Account Expire Prioritized with Round Robin (EAEP-RR) scheduling”, to handle the requests at cloud. At last, we can presume that our routines can advantage the scientific communities from the economies of scale in the cloud environment.