2011 IEEE Third International Conference on Cloud Computing Technology and Science最新文献_第10页

A Cloud Infrastructure for Collaborative Digital Public Services 协同数字公共服务的云基础设施

2011 IEEE Third International Conference on Cloud Computing Technology and Science Pub Date : 2011-11-29 DOI: 10.1109/CloudCom.2011.53

Y. Charalabidis, S. Koussouris, A. Ramfos

{"title":"A Cloud Infrastructure for Collaborative Digital Public Services","authors":"Y. Charalabidis, S. Koussouris, A. Ramfos","doi":"10.1109/CloudCom.2011.53","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.53","url":null,"abstract":"Looking back at the major developments of the previous years in the Internet and IT industry, it is more than certain that two of the most important innovations are cloud computing, which evidently takes processing power and IT provision to a whole new level, and Web2.0 service applications, that reveal the innovative thinking and development power of users, who in many cases are the architects of these applications. Despite this progress, focusing on the provision of public services reveals that until today little has been done in order to expose the real power of those two concepts. Cloud computing is in most cases regarded just as an alternative to having in premise infrastructures, while Web2.0 applications designed by third parties cannot be integrated in the public sector and are characterised as \"promising initiatives that cannot go further\". This paper targets the constantly increasing need for having more efficient and effective public sector services by trying to combine the benefits that derive by both the cloud computing and the open innovation concepts, and proposes a platform that could actually assist stakeholders to deploy their services towards meeting their needs, whether this refers to the exposure of public services over cloud infrastructures or to the creation of personalised composite public services.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131581007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Scalable and Low-Latency Data Processing with Stream MapReduce 流MapReduce的可扩展和低延迟数据处理

2011 IEEE Third International Conference on Cloud Computing Technology and Science Pub Date : 2011-11-29 DOI: 10.1109/CloudCom.2011.17

Andrey Brito, André Martin, Thomas Knauth, Stephan Creutz, D. Brum, Stefan Weigert, C. Fetzer

引用次数: 69

Energy Efficient Free Cooling System for Data Centers 数据中心节能自然冷却系统

2011 IEEE Third International Conference on Cloud Computing Technology and Science Pub Date : 2011-11-29 DOI: 10.1109/CloudCom.2011.100

Christy Sujatha D., Satheesh Abimannan

{"title":"Energy Efficient Free Cooling System for Data Centers","authors":"Christy Sujatha D., Satheesh Abimannan","doi":"10.1109/CloudCom.2011.100","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.100","url":null,"abstract":"A data center is a facility used to keep computer related equipments. It is estimated that heat production rate of the data center is doubled in every two years and hence the inevitability of the cooling system gets increased. In due course power consumption of a data center is augmented and more cost is spent on the power usage of the cooling system rather than the equipment purchase. As a result power savings for the cooling system is strongly desired. In this paper we conferred two primary free cooling systems namely air economizer and water economizer. A free cooling economizer system uses the outside air which is forced to the data center when outside climate is suitable to meet the ASHRE's cooling requirements. We have also conducted a survey and simulation based estimation using TRACE[TM] Chiller Plant Analyzer Tool. In this study, the energy consumption in a data center using conventional cooling system is compared with Air Economizer and Water Economizer for three different Zones namely Chicago, Atlanta and Phoenix in view of the fact that the outside air is relatively cool most of the year. From the projected result it is observed that both economizers reduce energy and cost when compared with conventional system and the usage of Economizer permits the chiller to shut down or reduce chiller energy load under suitable weather conditions. The results show that Water economizers are shown to consistently outperform air economizer which provides significant improvement in cooling system efficiency and cost at data center. The performance ratio of the conventional, air economizer and the water economizers are 50%, 76% and 79% respectively that shows economizers provide more savings relative to the conventional system.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134409392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 24

As Strong as the Weakest Link: Handling Compromised Components in OpenStack 像最薄弱的环节一样强大:处理OpenStack中的受损组件

2011 IEEE Third International Conference on Cloud Computing Technology and Science Pub Date : 2011-11-29 DOI: 10.1109/CloudCom.2011.34

Aryan TaheriMonfared, M. Jaatun

引用次数: 12

Scientific Workflow Makespan Reduction through Cloud Augmented Desktop Grids 通过云增强桌面网格减少科学的工作流程完工时间

2011 IEEE Third International Conference on Cloud Computing Technology and Science Pub Date : 2011-11-29 DOI: 10.1109/CloudCom.2011.13

Christopher J. Reynolds, S. Winter, G. Terstyánszky, T. Kiss, P. Greenwell, S. Ács, P. Kacsuk

{"title":"Scientific Workflow Makespan Reduction through Cloud Augmented Desktop Grids","authors":"Christopher J. Reynolds, S. Winter, G. Terstyánszky, T. Kiss, P. Greenwell, S. Ács, P. Kacsuk","doi":"10.1109/CloudCom.2011.13","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.13","url":null,"abstract":"Scientific workflows are common in biomedical research, particularly for molecular docking simulations such as those used in drug discovery. Such workflows typically involve data distribution between computationally demanding stages which are usually mapped onto large scale compute resources. Volunteer or Desktop Grid (DG) computing can provide such infrastructure but has limitations resulting from the heterogeneous nature of the compute nodes. These constraints mean that reducing the make span of a given workflow stage submitted to a DG becomes problematic. Late jobs can significantly affect the make span, often completing long after the bulk of the computation has finished. In this paper we present a system capable of significantly reducing the make span of a scientific workflow. Our system comprises a DG which is dynamically augmented with an infrastructure as a service (IaaS) Cloud. Using this solution, the Cloud resources are used to process replicated late jobs. Our system comprises a core component termed the scheduler, which implements an algorithm to perform late job detection, Cloud resource management (instantiation and reuse), and job monitoring. We offer a formal definition of this algorithm, whilst we also provide an evaluation of our prototype using a production scientific workflow.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132662966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 22

ViteraaS: Virtual Cluster as a Service ViteraaS:虚拟集群即服务

2011 IEEE Third International Conference on Cloud Computing Technology and Science Pub Date : 2011-11-29 DOI: 10.1109/CloudCom.2011.101

Frank Dölitzscher, Markus Held, C. Reich, Anthony Sulistio

引用次数: 32

A Business Resolution Engine for Cloud Marketplaces 云市场的业务解决方案引擎

2011 IEEE Third International Conference on Cloud Computing Technology and Science Pub Date : 2011-11-29 DOI: 10.1109/CLOUDCOM.2011.68

A. Menychtas, Anna Gatzioura, T. Varvarigou

引用次数: 26

Automating Application Deployment in Infrastructure Clouds 在基础设施云中自动化应用程序部署

2011 IEEE Third International Conference on Cloud Computing Technology and Science Pub Date : 2011-11-29 DOI: 10.1109/CloudCom.2011.102

G. Juve, E. Deelman

引用次数: 74

Applications Know Best: Performance-Driven Memory Overcommit with Ginkgo 应用程序知道最好的:性能驱动的内存过度使用银杏

2011 IEEE Third International Conference on Cloud Computing Technology and Science Pub Date : 2011-11-29 DOI: 10.1109/CloudCom.2011.27

M. R. Hines, Abel Gordon, Márcio Silva, D. D. Silva, K. D. Ryu, Muli Ben-Yehuda

{"title":"Applications Know Best: Performance-Driven Memory Overcommit with Ginkgo","authors":"M. R. Hines, Abel Gordon, Márcio Silva, D. D. Silva, K. D. Ryu, Muli Ben-Yehuda","doi":"10.1109/CloudCom.2011.27","DOIUrl":"https://doi.org/10.1109/CloudCom.2011.27","url":null,"abstract":"Memory over commitment enables cloud providers to host more virtual machines on a single physical server, exploiting spare CPU and I/O capacity when physical memory becomes the bottleneck for virtual machine deployment. However, over commiting memory can also cause noticeable application performance degradation. We present Ginkgo, a policy framework for over omitting memory in an informed and automated fashion. By directly correlating application-level performance to memory, Ginkgo automates the redistribution of scarce memory across all virtual machines, satisfying performance and capacity constraints. Ginkgo also achieves memory gains for traditionally fixed-size Java applications by coordinating the redistribution of available memory with the activities of the Java Virtual Machine heap. When compared to a non-over commited system, Ginkgo runs the Day Trader 2.0 and SPEC Web 2009 benchmarks with the same number of virtual machines while saving up to 73% (50% omitting free space) of a physical server's memory while keeping application performance degradation within 7%.","PeriodicalId":427190,"journal":{"name":"2011 IEEE Third International Conference on Cloud Computing Technology and Science","volume":"2017 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128058491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 72

Combinatorial Auction-Based Dynamic VM Provisioning and Allocation in Clouds 基于组合拍卖的云环境下虚拟机动态发放与分配

2011 IEEE Third International Conference on Cloud Computing Technology and Science Pub Date : 2011-11-12 DOI: 10.1145/2148600.2148658

Sharrukh Zaman, Daniel Grosu

引用次数: 82