2013 IEEE Sixth International Conference on Cloud Computing最新文献_第2页

Smart CloudBench -- Automated Performance Benchmarking of the Cloud 智能CloudBench——云的自动性能基准测试

2013 IEEE Sixth International Conference on Cloud Computing Pub Date : 2013-06-28 DOI: 10.1109/CLOUD.2013.7

Mohan Baruwal Chhetri, S. Chichin, Quoc Bao Vo, R. Kowalczyk

{"title":"Smart CloudBench -- Automated Performance Benchmarking of the Cloud","authors":"Mohan Baruwal Chhetri, S. Chichin, Quoc Bao Vo, R. Kowalczyk","doi":"10.1109/CLOUD.2013.7","DOIUrl":"https://doi.org/10.1109/CLOUD.2013.7","url":null,"abstract":"As the rate of cloud computing adoption grows, so does the need for consumption assistance. Enterprises that are looking to migrate their IT systems to the cloud, would like to quickly identify providers that offer resources with the most appropriate pricing and performance levels to match their specific business needs. However, no two vendors offer the same resource configurations, pricing and provisioning models, making the task of selecting appropriate computing resources complex, time-consuming and expensive. In this paper, we present Smart CloudBench - a platform that automates the performance benchmarking of cloud infrastructure, helping potential consumers quickly identify the cloud providers that can deliver the most appropriate price/performance levels to meet their specific requirements. Users can estimate the actual performance of the different cloud platforms by testing representative benchmark applications under representative load conditions. Experimentation using the prototype implementation shows that higher price does not necessarily translate to better or more consistent performance, and benchmarking results can provide more information to help enterprises make better informed decisions.","PeriodicalId":218844,"journal":{"name":"2013 IEEE Sixth International Conference on Cloud Computing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125772870","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: 40

A Declarative Environment for Automatic Performance Evaluation in IaaS Clouds IaaS云中用于自动性能评估的声明式环境

2013 IEEE Sixth International Conference on Cloud Computing Pub Date : 2013-06-28 DOI: 10.1109/CLOUD.2013.12

Matheus Cunha, N. Mendonça, Américo Sampaio

{"title":"A Declarative Environment for Automatic Performance Evaluation in IaaS Clouds","authors":"Matheus Cunha, N. Mendonça, Américo Sampaio","doi":"10.1109/CLOUD.2013.12","DOIUrl":"https://doi.org/10.1109/CLOUD.2013.12","url":null,"abstract":"One of the main challenges faced by users of infrastructure-as-a-service (IaaS) clouds is the difficulty to adequately estimate the virtual resources necessary for their applications. Although many cloud providers offer programatic ways to rapidly acquire and release resources, it is important that users have a prior understanding of the impact that each virtual resource type offered by the provider may impose on application performance. This paper presents Cloud Crawler, a new declarative environment aimed at supporting users in describing and automatically executing application performance tests in IaaS clouds. To this end, the environment provides a novel declarative domain-specific language, called Crawl, which supports the description of a variety of performance evaluation scenarios in multiple IaaS clouds, and an extensible Java-based cloud execution engine, called Crawler, which automatically configures, executes and collects the results of each performance evaluation scenario described in Crawl. To illustrate Cloud Crawler's potential benefits, the paper reports on an experimental evaluation of a social network application in two public IaaS cloud providers, in which the proposed environment has successfully been used to investigate the application performance for different virtual machine configurations and under different demand levels.","PeriodicalId":218844,"journal":{"name":"2013 IEEE Sixth International Conference on Cloud Computing","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129519134","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: 37

Privacy-Preserving Collaborative Filtering on the Cloud and Practical Implementation Experiences 云上保护隐私的协同过滤及其实践实现经验

2013 IEEE Sixth International Conference on Cloud Computing Pub Date : 2013-06-28 DOI: 10.1109/CLOUD.2013.109

A. Basu, Jaideep Vaidya, H. Kikuchi, T. Dimitrakos

引用次数: 16

QoS-Aware, Cost-Efficient Selection of Cloud Data Centers 云数据中心的质量意识、成本效益选择

2013 IEEE Sixth International Conference on Cloud Computing Pub Date : 2013-06-28 DOI: 10.1109/CLOUD.2013.113

Ronny Hans, Ulrich Lampe, R. Steinmetz

引用次数: 16

Framework for Assessing Cloud Trustworthiness 评估云可信度的框架

2013 IEEE Sixth International Conference on Cloud Computing Pub Date : 2013-06-28 DOI: 10.1109/CLOUD.2013.76

Curt Wu, Steve Marotta

引用次数: 5

Evaluation Criteria for Cloud Services 云服务评估标准

2013 IEEE Sixth International Conference on Cloud Computing Pub Date : 2013-06-28 DOI: 10.1109/CLOUD.2013.70

Pedro Costa, João Paulo Santos, M. Silva

引用次数: 24

Optimization of Electricity and Server Maintenance Costs in Hybrid Cooling Data Centers 混合冷却数据中心的电力和服务器维护成本优化

2013 IEEE Sixth International Conference on Cloud Computing Pub Date : 2013-06-28 DOI: 10.1109/CLOUD.2013.104

Shaoming Chen, Yue Hu, Lu Peng

引用次数: 8

Secure Outsourcing of Matrix Operations as a Service 矩阵操作即服务的安全外包

2013 IEEE Sixth International Conference on Cloud Computing Pub Date : 2013-06-28 DOI: 10.1109/CLOUD.2013.124

M. Nassar, A. Erradi, Farida Sabry, Q. Malluhi

引用次数: 12

MC2: Map Concurrency Characterization for MapReduce on the Cloud MC2:云上MapReduce的地图并发特性

2013 IEEE Sixth International Conference on Cloud Computing Pub Date : 2013-06-28 DOI: 10.1109/CLOUD.2013.93

Mohammad Hammoud, M. Sakr

{"title":"MC2: Map Concurrency Characterization for MapReduce on the Cloud","authors":"Mohammad Hammoud, M. Sakr","doi":"10.1109/CLOUD.2013.93","DOIUrl":"https://doi.org/10.1109/CLOUD.2013.93","url":null,"abstract":"MapReduce is now a pervasive analytics engine on the cloud. Hadoop is an open source implementation of MapReduce and is currently enjoying wide popularity. Hadoop offers a high-dimensional space of configuration parameters, which makes it difficult for practitioners to set for efficient and cost-effective execution. In this work we observe that MapReduce application performance is highly influenced by map concurrency. Map concurrency is defined in terms of two configurable parameters, the number of available map slots and the number of map tasks running over the slots. We show that some inherent MapReduce characteristics enable well-informed prediction of map concurrency. We propose Map Concurrency Characterization (MC2), a standalone utility program that can predict the best map concurrency for any given MapReduce application. By leveraging the generated predicted information, MC2 can judiciously guide Map phase configuration and, consequently, improve Hadoop performance. Unlike many of relevant schemes, MC2 does not employ simulation, dynamic instrumentation, and/or static analysis of unmodified job code to predict map concurrency. In contrast, MC2 utilizes a simple, yet effective mathematical model, which exploits the MapReduce characteristics that impact map concurrency. We implemented MC2 and conducted comprehensive experiments on a private cloud and on Amazon MC2 using Hadoop 0.20.2. Our results show that MC2 can correctly predict the best map concurrencies for the tested benchmarks and provide up to 2.2X speedup in runtime.","PeriodicalId":218844,"journal":{"name":"2013 IEEE Sixth International Conference on Cloud Computing","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116660389","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: 5

Residency Aware Inter-VM Communication in Virtualized Cloud: Performance Measurement and Analysis 虚拟化云中驻留感知的虚拟机间通信:性能测量与分析

2013 IEEE Sixth International Conference on Cloud Computing Pub Date : 2013-06-28 DOI: 10.1109/CLOUD.2013.116

Qi Zhang, Ling Liu, Yi Ren, Kisung Lee, Y. Tang, Xu Zhao, Yang Zhou

{"title":"Residency Aware Inter-VM Communication in Virtualized Cloud: Performance Measurement and Analysis","authors":"Qi Zhang, Ling Liu, Yi Ren, Kisung Lee, Y. Tang, Xu Zhao, Yang Zhou","doi":"10.1109/CLOUD.2013.116","DOIUrl":"https://doi.org/10.1109/CLOUD.2013.116","url":null,"abstract":"A known problem for virtualized cloud data centers is the inter-VM communication inefficiency for data transfer between co-resident VMs. Several engineering efforts have been made on building a shared memory based channel between co-resident VMs. The implementations differ in terms of whether user/program transparency, OS kernel transparency or VMM transparency is supported. However, none of existing works has engaged in an in-depth measurement study with quantitative and qualitative analysis on performance improvements as well as tradeoffs introduced by such a residency-aware inter-VM communication mechanism. In this paper we present an extensive experimental study, aiming at addressing a number of fundamental issues and providing deeper insights regarding the design of a shared memory channel for co-resident VMs. Example questions include how much performance gains can a residency-aware shared memory inter-VM communication mechanism provide under different mixtures of local and remote network I/O workloads, what overhead will the residence-awareness detection and communication channel switch introduce over the remote inter-VM communication, what factors may exert significant impact on the throughput and latency performance of such a shared memory channel. We believe that this measurement study not only helps system developers to gain valuable lessons and generate new ideas to further improve the inter-VM communication performance. It also offers new opportunities for cloud service providers to deploy their services more efficiently and for cloud service consumers to improve the performance of their application systems running in the Cloud.","PeriodicalId":218844,"journal":{"name":"2013 IEEE Sixth International Conference on Cloud Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131189172","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: 18