2010 IEEE Second International Conference on Cloud Computing Technology and Science最新文献_第3页

Exploring the Performance Fluctuations of HPC Workloads on Clouds 云环境下高性能计算工作负载的性能波动研究

2010 IEEE Second International Conference on Cloud Computing Technology and Science Pub Date : 2010-11-30 DOI: 10.1109/CloudCom.2010.84

Y. E. Khamra, Hyunjoo Kim, S. Jha, M. Parashar

引用次数: 63

Framing the Issues of Cloud Computing & Sustainability: A Design Perspective 构建云计算与可持续性问题:设计视角

2010 IEEE Second International Conference on Cloud Computing Technology and Science Pub Date : 2010-11-30 DOI: 10.1109/CloudCom.2010.77

Yue Pan, S. Maini, Eli Blevis

引用次数: 8

Do You Get What You Pay For? Using Proof-of-Work Functions to Verify Performance Assertions in the Cloud 你得到了你所付出的吗?使用工作量证明函数来验证云中的性能断言

2010 IEEE Second International Conference on Cloud Computing Technology and Science Pub Date : 2010-11-30 DOI: 10.1109/CloudCom.2010.100

Falk Koeppe, Jörg Schneider

{"title":"Do You Get What You Pay For? Using Proof-of-Work Functions to Verify Performance Assertions in the Cloud","authors":"Falk Koeppe, Jörg Schneider","doi":"10.1109/CloudCom.2010.100","DOIUrl":"https://doi.org/10.1109/CloudCom.2010.100","url":null,"abstract":"In the Cloud, the operators usually offer resources on a pay per use price model. The client gets access to a newly created virtual machine and has no direct access to the underlying hardware. Therefore, the client cannot verify whether the Cloud operator provides the negotiated amount of resources or only a fraction thereof. Especially, the assigned share of CPU time can be easily forged by the operator. The client could use a normal benchmark to verify the performance of his virtual machine. However, as the Cloud operator owns the underlying infrastructure, the operator could also tamper with the benchmark execution. We identified four attack vectors to modify the results of the benchmark. Based on these attack vectors, we showed that using proof-of-work functions can disable three of them. Proof-of-work functions are challenge response systems, where it is simple to generate a challenge and verify the result while solving the challenge is compute intensive. We implemented three proof-of-work functions in a prototype benchmark. Experiments showed that the runtime of the proof-of-work functions sufficiently relates to the results of the reference benchmark suite SPEC CPU2006.","PeriodicalId":130987,"journal":{"name":"2010 IEEE Second International Conference on Cloud Computing Technology and Science","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115151908","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: 15

Howdah - A Flexible Pipeline Framework for Analyzing Genomic Data Howdah -分析基因组数据的灵活管道框架

2010 IEEE Second International Conference on Cloud Computing Technology and Science Pub Date : 2010-11-30 DOI: 10.1109/CloudCom.2010.75

Steven Lewis, Sheila M. Reynolds, Hector Rovira, Mike O'Leary, S. Killcoyne, I. Shmulevich, J. Boyle

引用次数: 0

Correlation Based File Prefetching Approach for Hadoop 基于关联的Hadoop文件预取方法

2010 IEEE Second International Conference on Cloud Computing Technology and Science Pub Date : 2010-11-30 DOI: 10.1109/CloudCom.2010.60

B. Dong, Xiao Zhong, Q. Zheng, L. Jian, Jian Liu, J. Qiu, Ying Li

{"title":"Correlation Based File Prefetching Approach for Hadoop","authors":"B. Dong, Xiao Zhong, Q. Zheng, L. Jian, Jian Liu, J. Qiu, Ying Li","doi":"10.1109/CloudCom.2010.60","DOIUrl":"https://doi.org/10.1109/CloudCom.2010.60","url":null,"abstract":"Hadoop Distributed File System (HDFS) has been widely adopted to support Internet applications because of its reliable, scalable and low-cost storage capability. Blue Sky, one of the most popular e-Learning resource sharing systems in China, is utilizing HDFS to store massive courseware. However, due to the inefficient access mechanism of HDFS, access latency of reading files from HDFS significantly impacts the performance of processing user requests. This paper introduces a two-level correlation based file prefetching approach, taking the characteristics of HDFS into consideration, to improve performance by reducing access latency. Four placement patterns to store prefetched data are presented, with policies to achieve trade-off between performance and efficiency of HDFS prefetching. Moreover, a dynamic replica selection algorithm is investigated to improve the efficiency of HDFS prefetching. The proposed prefetching approach has been implemented in Blue Sky, and experimental results prove that correlation based file prefetching can significantly reduce access latency therefore improve performance of Hadoop-based Internet applications.","PeriodicalId":130987,"journal":{"name":"2010 IEEE Second International Conference on Cloud Computing Technology and Science","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125334141","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: 21

Exploratory Project: State of the Cloud, from University of Michigan and Beyond 探索性项目:云的状态，来自密歇根大学和其他大学

2010 IEEE Second International Conference on Cloud Computing Technology and Science Pub Date : 2010-11-30 DOI: 10.1109/CloudCom.2010.50

T. Ruthkoski

引用次数: 7

Using Global Behavior Modeling to Improve QoS in Cloud Data Storage Services 利用全局行为建模提高云数据存储服务的QoS

2010 IEEE Second International Conference on Cloud Computing Technology and Science Pub Date : 2010-11-30 DOI: 10.1109/CloudCom.2010.33

Jesús Montes, Bogdan Nicolae, Gabriel Antoniu, Alberto Sánchez, María S. Pérez

{"title":"Using Global Behavior Modeling to Improve QoS in Cloud Data Storage Services","authors":"Jesús Montes, Bogdan Nicolae, Gabriel Antoniu, Alberto Sánchez, María S. Pérez","doi":"10.1109/CloudCom.2010.33","DOIUrl":"https://doi.org/10.1109/CloudCom.2010.33","url":null,"abstract":"The cloud computing model aims to make large-scale data-intensive computing affordable even for users with limited financial resources, that cannot invest into expensive infrastructures necesssary to run them. In this context, MapReduce is emerging as a highly scalable programming paradigm that enables high-throughput data-intensive processing as a cloud service. Its performance is highly dependent on the underlying storage service, responsible to efficiently support massively parallel data accesses by guaranteeing a high throughput under heavy access concurrency. In this context, quality of service plays a crucial role: the storage service needs to sustain a stable throughput for each individual accesss, in addition to achieving a high aggregated throughput under concurrency. In this paper we propose a technique to address this problem using component monitoring, application-side feedback and behavior pattern analysis to automatically infer useful knowledge about the causes of poor quality of service and provide an easy way to reason in about potential improvements. We apply our proposal to Blob Seer, a representative data storage service specifically designed to achieve high aggregated throughputs and show through extensive experimentation substantial improvements in the stability of individual data read accesses under MapReduce workloads.","PeriodicalId":130987,"journal":{"name":"2010 IEEE Second International Conference on Cloud Computing Technology and Science","volume":"230 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117341136","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

Abstractions for Loosely-Coupled and Ensemble-Based Simulations on Azure Azure上松散耦合和基于集成的模拟的抽象

2010 IEEE Second International Conference on Cloud Computing Technology and Science Pub Date : 2010-11-30 DOI: 10.1109/CloudCom.2010.85

André Luckow, S. Jha

引用次数: 17

Social Impact of Privacy in Cloud Computing 云计算中隐私的社会影响

2010 IEEE Second International Conference on Cloud Computing Technology and Science Pub Date : 2010-11-30 DOI: 10.1109/CloudCom.2010.98

R. Esteves, Chunming Rong

引用次数: 19

Sustainable Network Resource Management System for Virtual Private Clouds 面向虚拟私有云的可持续网络资源管理系统

2010 IEEE Second International Conference on Cloud Computing Technology and Science Pub Date : 2010-11-30 DOI: 10.1109/CloudCom.2010.63

T. Miyamoto, M. Hayashi, Kosuke Nishimura

引用次数: 31