2014 IEEE 7th International Conference on Cloud Computing最新文献

Cloudburst - Simulating Workload for IaaS Clouds Cloudburst -模拟IaaS云的工作负载

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.116

J. Kross, A. Wolke

引用次数: 5

Towards a Flexible Fine-Grained Access Control System for Modern Cloud Applications 面向现代云应用的灵活细粒度访问控制系统

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.144

Reza Shiftehfar, K. Mechitov, G. Agha

引用次数: 5

Smart CloudMonitor - Providing Visibility into Performance of Black-Box Clouds 智能CloudMonitor -提供对黑盒子云性能的可见性

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.108

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

{"title":"Smart CloudMonitor - Providing Visibility into Performance of Black-Box Clouds","authors":"Mohan Baruwal Chhetri, S. Chichin, Quoc Bao Vo, R. Kowalczyk","doi":"10.1109/CLOUD.2014.108","DOIUrl":"https://doi.org/10.1109/CLOUD.2014.108","url":null,"abstract":"Migration to the cloud offers several benefits including reduced operational costs, flexibility, scalability, and a greater focus on business goals, but it also has a flip side reduced visibility. Organizations only have a blackbox view of cloud servers and while pricing and specification information is publicly available, there is limited information about cloud performance. This necessitates the need for tools that can provide greater visibility into cloud insfrastructure performance so that consumers can objectively compare and contrast the offerings from different providers. Smart CloudBench [1][2][3] is a system that allows users to run automated, ondemand, real-time and customized benchmark tests on cloud infrastructure. In this paper, we present Smart CloudMonitor - a performance monitoring tool that provides multi-layer performance monitoring capabilities to Smart CloudBench. It provides greater visibility and insight into cloud performance by monitoring both application performance as well as the corresponding resource consumption. Experiments conducted on cloud infrastructure using Smart CloudBench show the add value that Smart CloudMonitor provides to the process of cloud performance evaluation.","PeriodicalId":288542,"journal":{"name":"2014 IEEE 7th International Conference on Cloud Computing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126057659","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: 8

Cost of Tape versus Disk for Archival Storage 用于归档存储的磁带与磁盘的成本

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.37

Jeff T. Inman, G. Grider, Hsing-bung Chen

引用次数: 5

Enhanced Backfill Computing 增强的回填计算

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.140

D. Che, J. Fairfield, P. Ghodous, Jean-Patrick Gelas

引用次数: 0

Multiple Two-Phase Data Processing with MapReduce MapReduce的多两阶段数据处理

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.55

Hsiang-Huang Wu, Tse-Chen Yeh, Chien-Min Wang

{"title":"Multiple Two-Phase Data Processing with MapReduce","authors":"Hsiang-Huang Wu, Tse-Chen Yeh, Chien-Min Wang","doi":"10.1109/CLOUD.2014.55","DOIUrl":"https://doi.org/10.1109/CLOUD.2014.55","url":null,"abstract":"MapReduce, proposed as a programming model, has been widely adopted in the field of text processing over large datasets with the capability of exploiting the distributed resources and processing the large-scale data. Attributed to its simplicity and scalability, the success seems to have the potential to make Big Data processing by cloud computing available. Nevertheless, such promise is accompanied by the difficulty of fitting the applications into MapReduce. This is because MapReduce is limited to the kind of applications that every input key-value pair is independent of each other. In this paper, we extend the general applicability of MapReduce by allowing the dependence within a set of input key-value pairs but preserving independence among all sets. Such this new modeling paradigm intends MapReduce to shift processing the independent input key-value pairs to processing the independent sets. However, the advancement in the applicability brings the intricate problem of how two-stage processing structure, inherent in MapReduce, handles the dependence within a set of input key-value pairs. To tackle this problem, we propose the design pattern called two-phase data processing. It expresses the application in two phases not only to match the two-stage processing structure but to exploit the power of MapReduce through the cooperation between the mappers and reducers. In addition, we present the design methodology-multiple two-phase data processing-to offer advice on processing the independent sets. The experiment of background subtraction, a part of video surveillance, proves that the new modeling paradigm broadens the possibilities of MapReduce and demonstrates how our design methodology guides the applications to the implementation.","PeriodicalId":288542,"journal":{"name":"2014 IEEE 7th International Conference on Cloud Computing","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129203756","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: 3

An Aspect-Oriented Approach to SLA-Driven Monitoring Multi-tenant Cloud Application 面向方面的sla驱动的多租户云应用监控方法

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.118

Huihong He, Zhiyi Ma, Hongjie Chen, Chih-Yi Yeh, W. Shao

{"title":"An Aspect-Oriented Approach to SLA-Driven Monitoring Multi-tenant Cloud Application","authors":"Huihong He, Zhiyi Ma, Hongjie Chen, Chih-Yi Yeh, W. Shao","doi":"10.1109/CLOUD.2014.118","DOIUrl":"https://doi.org/10.1109/CLOUD.2014.118","url":null,"abstract":"As more and more multi-tenant applications emerge in clouds, people increasingly recognize the importance of multi-tenant applications in realizing cloud benefit maximization. Service Level Agreement (SLA) is advocated widely to monitor these applications for multiple tenants to meet their service quality requirements. However, so far these applications provide limited multi-tenant monitoring supports, which prevents the applications from guaranteeing tenants' interests efficiently. In this paper, we propose an aspect-oriented approach to monitor multi-tenant applications based on tenant SLAs. Our approach includes monitoring code generation and runtime management. During code generation, the approach proposes an SLA feature model for tenants to specify variable requirements. Based on the requirements the approach selects code snippets, which are implemented as templates in advance, and splices them into an monitoring aspect. During runtime, the approach prioritizes aspects to determine execution order and updates monitoring status in term of tenant. An implemented prototype is used to evaluate the approach by case studies, which demonstrate the approach effectiveness in common situations.","PeriodicalId":288542,"journal":{"name":"2014 IEEE 7th International Conference on Cloud Computing","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123996452","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: 4

Use of Network Latency Profiling and Redundancy for Cloud Server Selection 使用网络延迟分析和冗余云服务器选择

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.114

Minseok Kwon, Zuochao Dou, W. Heinzelman, T. Soyata, He Ba, Jiye Shi

{"title":"Use of Network Latency Profiling and Redundancy for Cloud Server Selection","authors":"Minseok Kwon, Zuochao Dou, W. Heinzelman, T. Soyata, He Ba, Jiye Shi","doi":"10.1109/CLOUD.2014.114","DOIUrl":"https://doi.org/10.1109/CLOUD.2014.114","url":null,"abstract":"As servers are placed in diverse locations in networked services today, it becomes vital to direct a client's request to the best server(s) to achieve both high performance and reliability. In this distributed setting, non-negligible latency and server availability become two major concerns, especially for highly-interactive applications. Profiling latencies and sending redundant data have been investigated as solutions to these issues. The notion of a cloudlet in mobile-cloud computing is also relevant in this context, as the cloudlet can supply these solution approaches on behalf of the mobile. In this paper, we investigate the effects of profiling and redundancy on latency when a client has a choice of multiple servers to connect to, using measurements from real experiments and simulations. We devise and test different server selection and data partitioning strategies in terms of profiling and redundancy. Our key findings are summarized as follows. First, intelligent server selection algorithms help find the optimal group of servers that minimize latency with profiling. Second, we can achieve good performance with relatively simple approaches using redundancy. Our analysis of profiling and redundancy provides insight to help designers determine how many servers and which servers to select to reduce latency.","PeriodicalId":288542,"journal":{"name":"2014 IEEE 7th International Conference on Cloud Computing","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121310726","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: 53

A Comparative Study on I/O Performance between Compute and Storage Optimized Instances of Amazon EC2 Amazon EC2计算与存储优化实例I/O性能比较研究

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.146

Abu Awal Md Shoeb, Ragib Hasan, Munirul M. Haque, Meng-Zeng Hu

引用次数: 1

D-Mash: A Framework for Privacy-Preserving Data-as-a-Service Mashups D-Mash:一个保护隐私的数据即服务mashup框架

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.73

M. Arafati, Gaby G. Dagher, B. Fung, P. Hung

引用次数: 19