2012 IEEE Fifth International Conference on Utility and Cloud Computing最新文献_第4页

Risk and Energy Consumption Tradeoffs in Cloud Computing Service via Stochastic Optimization Models 基于随机优化模型的云计算服务风险与能耗权衡

2012 IEEE Fifth International Conference on Utility and Cloud Computing Pub Date : 2012-11-05 DOI: 10.1109/UCC.2012.37

Jue Wang, Siqian Shen

{"title":"Risk and Energy Consumption Tradeoffs in Cloud Computing Service via Stochastic Optimization Models","authors":"Jue Wang, Siqian Shen","doi":"10.1109/UCC.2012.37","DOIUrl":"https://doi.org/10.1109/UCC.2012.37","url":null,"abstract":"Energy efficiency and computational reliability are two key concerns associated with modern computations that involve computational resource sharing and highly uncertain job arrivals from various sources (customers). In 2010, large-scale data center operations consume around 2% of the total energy use in the US. Meanwhile, the development of cloud computing in the IT industry possesses great potential for lowering energy consumption by partitioning and scheduling job requests among multiple computational servers. In this paper, we formulate stochastic integer programming models to minimize energy consumption of cloud computing servers over finite time periods, while maintaining a pre-specified quality of service (QoS) level for satisfying uncertain computational requests. The models dynamically monitor and predict customer requests for each period, and proactively switch servers on/off according to estimated customer requests. QoS levels are maintained by either enforcing zero unsatisfied requests, or imposing a joint chance constraint to bound possible failures in a backlogging model. When uncertain requests follow continuous distributions, we employ the Sampling Average Approximation for generating scenario-based requests. Such an approach transforms the original probabilistic model into deterministic mixed-integer linear programs. We further demonstrate computational results of all models by testing instances with different parameter combinations, and investigate how backlogging, unit penalty cost and QoS levels influence computational performances and optimal solutions.","PeriodicalId":122639,"journal":{"name":"2012 IEEE Fifth International Conference on Utility and Cloud Computing","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130907840","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

Stochastic Tail-Phase Optimization for Bag-of-Tasks Execution in Clouds 云中任务袋执行的随机尾相位优化

2012 IEEE Fifth International Conference on Utility and Cloud Computing Pub Date : 2012-11-05 DOI: 10.1109/UCC.2012.23

Ana Oprescu, T. Kielmann, H. Leahu

{"title":"Stochastic Tail-Phase Optimization for Bag-of-Tasks Execution in Clouds","authors":"Ana Oprescu, T. Kielmann, H. Leahu","doi":"10.1109/UCC.2012.23","DOIUrl":"https://doi.org/10.1109/UCC.2012.23","url":null,"abstract":"Elastic applications like bags of tasks benefit greatly from Infrastructure as a Service (IaaS) clouds that let users allocate compute resources on demand, charging based on reserved time intervals. Users, however, still need guidance for mapping their applications onto multiple IaaS offerings, both minimizing execution time and respecting budget limitations. For budget-controlled execution of bags of tasks, we built Bats, a scheduler that estimates possible budget and make spancombinations using a tiny task sample, and then executes a bag within the user's budget constraints. Previous work has shown the efficacy of this approach. There remains, however, the risk of outlier tasks causing the execution to exceed the predicted make span. In this work, we present a stochastic optimization of the tail phase for Bats' execution. The main idea is to use the otherwise idling machines up until the end of their (already paid-for) allocation time. Using the task completion time information acquired during the execution, BaTS decides which tasks to replicate onto idle machines in the tail phase, reducing the make span and improving the tolerance to outlier tasks. Our evaluation results show that this effect is robust w.r.t. the quality of runtime predictions and is the strongest with more expensive schedules in which many fast machines are available.","PeriodicalId":122639,"journal":{"name":"2012 IEEE Fifth International Conference on Utility and Cloud Computing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125779833","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: 35

Tackling Insider Threat in Cloud Relational Databases 解决云关系数据库中的内部威胁

2012 IEEE Fifth International Conference on Utility and Cloud Computing Pub Date : 2012-11-05 DOI: 10.1109/UCC.2012.18

Qussai M. Yaseen, B. Panda

引用次数: 16

BlueShield: A Layer 2 Appliance for Enhanced Isolation and Security Hardening among Multi-tenant Cloud Workloads BlueShield:用于在多租户云工作负载中增强隔离和安全加固的第2层设备

2012 IEEE Fifth International Conference on Utility and Cloud Computing Pub Date : 2012-11-05 DOI: 10.1109/UCC.2012.21

Saurabh Barjatiya, P. Saripalli

{"title":"BlueShield: A Layer 2 Appliance for Enhanced Isolation and Security Hardening among Multi-tenant Cloud Workloads","authors":"Saurabh Barjatiya, P. Saripalli","doi":"10.1109/UCC.2012.21","DOIUrl":"https://doi.org/10.1109/UCC.2012.21","url":null,"abstract":"Enhanced Isolation and Security (EIS) in a cloud are of significant concern. Many organizations are hesitant in migrating to a cloud based infrastructure due to the perceived limitations with EIS. Earlier, we had presented the quantitative risk and impact assessment framework (QUIRC) [1]. QUIRC can be used to assess the security risks associated with the cloud computing platforms. In the present work, design and implementation of Blue Shield is presented. Blue Shield is a Layer2 appliance for an EIS hardening among multi-tenant cloud workloads. Blue Shield architecture provides EIS, significantly reducing the threats faced by the tenants in a cloud environment. EIS provided by Blue Shield is validated using a proof of concept implementation. Then shortcomings of the various present approaches in addressing the identified security threats are explained. It is shown that the present security applications, deployed in a non-cloud environment, do not require modification during migration to Blue Shield based clouds. Furthermore, the proposed design provides high level of protection among the VMs in the same VLAN.","PeriodicalId":122639,"journal":{"name":"2012 IEEE Fifth International Conference on Utility and Cloud Computing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130637302","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: 7

Cloud Deployment Model Selection Assessment for SMEs: Renting or Buying a Cloud 中小企业云部署模式选择评估:租用或购买云

2012 IEEE Fifth International Conference on Utility and Cloud Computing Pub Date : 2012-11-05 DOI: 10.1109/UCC.2012.29

J. Keung, F. Kwok

{"title":"Cloud Deployment Model Selection Assessment for SMEs: Renting or Buying a Cloud","authors":"J. Keung, F. Kwok","doi":"10.1109/UCC.2012.29","DOIUrl":"https://doi.org/10.1109/UCC.2012.29","url":null,"abstract":"Cloud computing technology is increasingly important in the industry with the promise of increased performance, dynamic resource allocation capabilities and provides a convincing opportunity for organizations to outsource their IT infrastructure under the pay-per-use model offered by many public cloud providers. But there are concerns when selecting between the private cloud and the public cloud that must be taken into account. Many SME enterprises with scarce in-house IT support and limited knowledge about different cloud technologies encounter difficulties in making the most appropriate choice on 'buying' a private cloud or 'renting' a public cloud service. Through a number of interviews with potential cloud adopters from the industry, this paper identifies the most relevant factors concerning cloud adoption and develops a cloud deployment model assessment method called Cloud Deployment Selection Model (CDSM). The model has been validated in real case studies, and recommendations derived have been compared with real adoption cases. Result shows it is able to accurately recommend a suitable cloud deployment model based on the factors identified from many SME organizations, an important tool for SMEs to decide between the private or the public cloud solution.","PeriodicalId":122639,"journal":{"name":"2012 IEEE Fifth International Conference on Utility and Cloud Computing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133728059","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: 17

Adapting MPI to MapReduce PaaS Clouds: An Experiment in Cross-Paradigm Execution 将MPI应用于MapReduce PaaS云:跨范式执行的实验

2012 IEEE Fifth International Conference on Utility and Cloud Computing Pub Date : 2012-11-05 DOI: 10.1109/UCC.2012.52

Jaroslaw Slawinski, V. Sunderam

引用次数: 8

Unsupervised Neural Predictor to Auto-administrate the Cloud Infrastructure 自动管理云基础设施的无监督神经预测器

2012 IEEE Fifth International Conference on Utility and Cloud Computing Pub Date : 2012-11-05 DOI: 10.1109/UCC.2012.35

Hanen Chihi, Walid Chainbi, K. Ghédira

引用次数: 5

Privacy Enhanced Pixel-Level Image Processing in the Clouds 隐私增强的云中的像素级图像处理

2012 IEEE Fifth International Conference on Utility and Cloud Computing Pub Date : 2012-11-05 DOI: 10.1109/UCC.2012.13

Arash Nourian, Muthucumaru Maheswaran

引用次数: 1

An Event Driven Multi-agent Architecture for Enabling Cloud Governance 支持云治理的事件驱动多代理体系结构

2012 IEEE Fifth International Conference on Utility and Cloud Computing Pub Date : 2012-11-05 DOI: 10.1109/UCC.2012.50

V. Munteanu, Teodor-Florin Fortiş, V. Negru

引用次数: 8

A Survey on Cloud Computing Elasticity 云计算弹性研究综述

2012 IEEE Fifth International Conference on Utility and Cloud Computing Pub Date : 2012-11-05 DOI: 10.1109/UCC.2012.30

Guilherme Galante, L. C. E. Bona

引用次数: 300