2010 IEEE 3rd International Conference on Cloud Computing最新文献_第6页

FlexPRICE: Flexible Provisioning of Resources in a Cloud Environment FlexPRICE:在云环境中灵活地提供资源

2010 IEEE 3rd International Conference on Cloud Computing Pub Date : 2010-07-05 DOI: 10.1109/CLOUD.2010.71

T. Henzinger, Anmol V. Singh, Vasu Singh, Thomas Wies, D. Zufferey

{"title":"FlexPRICE: Flexible Provisioning of Resources in a Cloud Environment","authors":"T. Henzinger, Anmol V. Singh, Vasu Singh, Thomas Wies, D. Zufferey","doi":"10.1109/CLOUD.2010.71","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.71","url":null,"abstract":"Cloud computing aims to give users virtually unlimited pay-per-use computing resources without the burden of managing the underlying infrastructure. We claim that, in order to realize the full potential of cloud computing, the user must be presented with a pricing model that offers flexibility at the requirements level, such as a choice between different degrees of execution speed and the cloud provider must be presented with a programming model that offers flexibility at the execution level, such as a choice between different scheduling policies. In such a flexible framework, with each job, the user purchases a virtual computer with the desired speed and cost characteristics, and the cloud provider can optimize the utilization of resources across a stream of jobs from different users. We designed a flexible framework to test our hypothesis, which is called FlexPRICE (Flexible Provisioning of Resources in a Cloud Environment) and works as follows. A user presents a job to the cloud. The cloud finds different schedules to execute the job and presents a set of quotes to the user in terms of price and duration for the execution. The user then chooses a particular quote and the cloud is obliged to execute the job according to the chosen quote. FlexPRICE thus hides the complexity of the actual scheduling decisions from the user, but still provides enough flexibility to meet the users actual demands. We implemented FlexPRICE in a simulator called PRICES that allows us to experiment with our framework. We observe that FlexPRICE provides a wide range of execution options --from fast and expensive to slow and cheap-- for the whole spectrum of data-intensive and computation-intensive jobs. We also observe that the set of quotes computed by FlexPRICE do not vary as the number of simultaneous jobs increases.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132594927","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: 58

Performance Measurements and Analysis of Network I/O Applications in Virtualized Cloud 虚拟化云中网络I/O应用的性能测量与分析

2010 IEEE 3rd International Conference on Cloud Computing Pub Date : 2010-07-05 DOI: 10.1109/CLOUD.2010.74

Yiduo Mei, Ling Liu, Xing Pu, Sankaran Sivathanu

引用次数: 91

Metadata Partitioning for Large-Scale Distributed Storage Systems 大规模分布式存储系统的元数据分区

2010 IEEE 3rd International Conference on Cloud Computing Pub Date : 2010-07-05 DOI: 10.1109/CLOUD.2010.24

Jan-Jan Wu, Pangfeng Liu, Y. Chung

引用次数: 20

Autonomic Management of Cloud Service Centers with Availability Guarantees 具有可用性保证的云服务中心自治管理

2010 IEEE 3rd International Conference on Cloud Computing Pub Date : 2010-07-05 DOI: 10.1109/CLOUD.2010.19

B. Addis, D. Ardagna, B. Panicucci, Li Zhang

引用次数: 81

Characterizing Cloud Federation for Enhancing Providers' Profit 表征云联盟以提高供应商利润

2010 IEEE 3rd International Conference on Cloud Computing Pub Date : 2010-07-05 DOI: 10.1109/CLOUD.2010.32

Íñigo Goiri, Jordi Guitart, J. Torres

{"title":"Characterizing Cloud Federation for Enhancing Providers' Profit","authors":"Íñigo Goiri, Jordi Guitart, J. Torres","doi":"10.1109/CLOUD.2010.32","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.32","url":null,"abstract":"Cloud federation has been proposed as a new paradigm that allows providers to avoid the limitation of owning only a restricted amount of resources, which forces them to reject new customers when they have not enough local resources to fulfill their customers' requirements. Federation allows a provider to dynamically outsource resources to other providers in response to demand variations. It also allows a provider that has underused resources to rent part of them to other providers. Both things could make the provider to get more profit when used adequately. This requires that the provider has a clear understanding of the potential of each federation decision, in order to choose the most convenient depending on the environment conditions. In this paper, we present a complete characterization of providers' federation in the Cloud, including decision equations to outsource resources to other providers, rent free resources to other providers (i.e. insourcing), or shutdown unused nodes to save power, and we characterize these decisions as a function of several parameters. Then, we demonstrate in the evaluation section how a provider can enhance its profit by using these equations to exploit federation, and how the different parameters influence which is the best decision on each situation.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133272200","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: 205

Adaptive Data Migration in Multi-tiered Storage Based Cloud Environment 基于多层存储的云环境下的自适应数据迁移

2010 IEEE 3rd International Conference on Cloud Computing Pub Date : 2010-07-05 DOI: 10.1109/CLOUD.2010.60

Gong Zhang, Lawrence Chiu, Ling Liu

{"title":"Adaptive Data Migration in Multi-tiered Storage Based Cloud Environment","authors":"Gong Zhang, Lawrence Chiu, Ling Liu","doi":"10.1109/CLOUD.2010.60","DOIUrl":"https://doi.org/10.1109/CLOUD.2010.60","url":null,"abstract":"Multi-tiered storage systems today are integrating Solid State Disks (SSD) on top of traditional rotational hard disks for performance enhancement due to the significant IO improvements in SSD technology. It is widely recognized that automated data migration between SSD and HDD plays a critical role in effective integration of SSD into multi-tiered storage systems. Furthermore, effective data migration has to take into account of application specific workload characteristics, deadlines, and IO profiles. An important and interesting challenge for automated data migration in multi-tiered storage systems is how to fully release the power of data migration while guaranteeing the migration deadline is critical to maximizing the performance of SSD-enabled multi-tiered storage system. In this paper, we present an adaptive look ahead data migration model that can incorporate application specific characteristics and I/O profiles as well as workload deadlines. Our adaptive data migration model has three unique features. First, it incorporates a set of key factors that may impact on the performance of look ahead migration efficiency in our formal model develop. Second, our data migration model can adaptively determine the optimal look ahead window size, based on several parameters, to optimize the effectiveness of look ahead migration. Third, we formally and experimentally show that the adaptive data migration model can improve overall system performance and resource utilization while meeting workload deadlines. Through our trace driven experimental study, we compare the adaptive look ahead migration approach with the basic migration model and show that the adaptive migration model is effective and efficient for continuously improving and tuning of the performance and scalability of multi-tier storage systems.","PeriodicalId":375404,"journal":{"name":"2010 IEEE 3rd International Conference on Cloud Computing","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114245667","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: 65

IRain: A Personal Storage Cloud for Integrating Web Data Services IRain:用于集成Web数据服务的个人存储云

2010 IEEE 3rd International Conference on Cloud Computing Pub Date : 2010-07-05 DOI: 10.1109/CLOUD.2010.43

Jiangning Cui, Taoying Liu, Qian Chen, Hong Liu

引用次数: 1

An Architecture for a Mashup Container in Virtualized Environments 虚拟化环境中Mashup容器的体系结构

2010 IEEE 3rd International Conference on Cloud Computing Pub Date : 2010-07-05 DOI: 10.1109/CLOUD.2010.34

Michele Stecca, M. Maresca

引用次数: 11

A Runtime Model Based Monitoring Approach for Cloud 一种基于运行时模型的云监控方法

2010 IEEE 3rd International Conference on Cloud Computing Pub Date : 2010-07-05 DOI: 10.1109/CLOUD.2010.31

Jin Shao, Hao Wei, Qianxiang Wang, Hong Mei

引用次数: 132

Fault Tolerance Middleware for Cloud Computing 云计算容错中间件

2010 IEEE 3rd International Conference on Cloud Computing Pub Date : 2010-07-05 DOI: 10.1109/CLOUD.2010.26

Wenbing Zhao, P. Melliar-Smith, L. Moser

引用次数: 179