2016 IEEE International Conference on Cloud Engineering (IC2E)最新文献

Cloud Instance Management and Resource Prediction for Computation-as-a-Service Platforms 计算即服务平台的云实例管理与资源预测

2016 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2016-04-16 DOI: 10.1109/IC2E.2016.36

Joseph Doyle, V. Giotsas, M. A. Anam, Y. Andreopoulos

{"title":"Cloud Instance Management and Resource Prediction for Computation-as-a-Service Platforms","authors":"Joseph Doyle, V. Giotsas, M. A. Anam, Y. Andreopoulos","doi":"10.1109/IC2E.2016.36","DOIUrl":"https://doi.org/10.1109/IC2E.2016.36","url":null,"abstract":"Computation-as-a-Service (CaaS) offerings have gained traction in the last few years due to their effectiveness in balancing between the scalability of Software-as-a-Service and the customisation possibilities of Infrastructure-as-a-Service platforms. To function effectively, a CaaS platform must have three key properties: (i) reactive assignment of individual processing tasks to available cloud instances (compute units) according to availability and predetermined time-to-completion (TTC) constraints, (ii) accurate resource prediction, (iii) efficient control of the number of cloud instances servicing workloads, in order to optimize between completing workloads in a timely fashion and reducing resource utilization costs. In this paper, we propose three approaches that satisfy these properties (respectively): (i) a service rate allocation mechanism based on proportional fairness and TTC constraints, (ii) Kalman-filter estimates for resource prediction, and (iii) the use of additive increase multiplicative decrease (AIMD) algorithms (famous for being the resource management in the transport control protocol) for the control of the number of compute units servicing workloads. The integration of our three proposals into a single CaaS platform is shown to provide for more than 27% reduction in Amazon EC2 spot instance cost against methods based on reactive resource prediction and 38% to 60% reduction of the billing cost against the current state-of-the-art in CaaS platforms (Amazon Lambda and Autoscale).","PeriodicalId":430893,"journal":{"name":"2016 IEEE International Conference on Cloud Engineering (IC2E)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129778727","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: 9

Building Compliance and Security Reference Architectures (CSRA) for Cloud Systems 为云系统构建遵从性和安全性参考架构(CSRA)

2016 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2016-04-04 DOI: 10.1109/IC2E.2016.16

D. Yimam, E. Fernández

引用次数: 6

Information Flow Audit for PaaS Clouds PaaS云的信息流审计

2016 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2016-04-04 DOI: 10.1109/IC2E.2016.19

Thomas Pasquier, Jatinder Singh, J. Bacon, D. Eyers

{"title":"Information Flow Audit for PaaS Clouds","authors":"Thomas Pasquier, Jatinder Singh, J. Bacon, D. Eyers","doi":"10.1109/IC2E.2016.19","DOIUrl":"https://doi.org/10.1109/IC2E.2016.19","url":null,"abstract":"With the rapid increase in uptake of cloud services, issues of data management are becoming increasingly prominent. There is a clear, outstanding need for the ability for specified policy to control and track data as it flows throughout cloud infrastructure, to ensure that those responsible for data are meeting their obligations. This paper introduces Information Flow Audit, an approach for tracking information flows within cloud infrastructure. This builds upon CamFlow (Cambridge Flow Control Architecture), a prototype implementation of our model for data-centric security in PaaS clouds. CamFlow enforces Information Flow Control policy both intra-machine at the kernel-level, and inter-machine, on message exchange. Here we demonstrate how CamFlow can be extended to provide data-centric audit logs akin to provenance metadata in a format in which analyses can easily be automated through the use of standard graph processing tools. This allows detailed understanding of the overall system. Combining a continuously enforced data-centric security mechanism with meaningful audit empowers tenants and providers to both meet and demonstrate compliance with their data management obligations.","PeriodicalId":430893,"journal":{"name":"2016 IEEE International Conference on Cloud Engineering (IC2E)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126069250","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: 30

Surviving Failures with Performance-Centric Bandwidth Allocation in Private Datacenters 在私有数据中心以性能为中心的带宽分配中幸存故障

2016 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2016-04-04 DOI: 10.1109/IC2E.2016.34

Li Chen, Baochun Li, Bo Li

{"title":"Surviving Failures with Performance-Centric Bandwidth Allocation in Private Datacenters","authors":"Li Chen, Baochun Li, Bo Li","doi":"10.1109/IC2E.2016.34","DOIUrl":"https://doi.org/10.1109/IC2E.2016.34","url":null,"abstract":"In the context of private datacenters that are operated by Web service providers such as Google, multiple applications using data parallel frameworks, such as MapReduce, coexist and share a limited supply of link bandwidth capacities. It has been shown that failures are the norm, rather than the exception, in datacenters, and will negatively affect the performance of data parallel applications as failed tasks need to be relaunched and placed on newly selected servers. In this paper, we argue that even with the presence of failures, link bandwidth should be allocated to competing applications with performance-centric fairness, in that the performance that applications enjoy should be proportional to their weights. We formulate and solve the open challenge of jointly optimizing placement decisions for relaunched tasks and bandwidth allocation, so that the adverse effects of failures on application performance are minimized. With our proposed algorithm implemented in the Mininet emulation testbed, our experiments show the effectiveness of our solutions towards minimizing the negative effects of failures, while still achieving performance-centric fairness.","PeriodicalId":430893,"journal":{"name":"2016 IEEE International Conference on Cloud Engineering (IC2E)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134019842","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: 6

IoT End-User Applications Provisioning in the Cloud: State of the Art 云中的物联网最终用户应用程序配置:最新进展

2016 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2016-04-04 DOI: 10.1109/IC2E.2016.43

Sami Yangui, R. Glitho, F. Belqasmi, M. Morrow, P. Polakos

引用次数: 4

Exploring the Use of Tags for Georeplicated Content Placement 探索标签在地理复制内容放置中的使用

2016 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2016-04-04 DOI: 10.1109/IC2E.2016.37

Stéphane Delbruel, Davide Frey, François Taïani

{"title":"Exploring the Use of Tags for Georeplicated Content Placement","authors":"Stéphane Delbruel, Davide Frey, François Taïani","doi":"10.1109/IC2E.2016.37","DOIUrl":"https://doi.org/10.1109/IC2E.2016.37","url":null,"abstract":"A large portion of today's Internet traffic originates from streaming and video services. Such services rely on a combination of distributed datacenters, powerful content delivery networks (CDN), and multi-level caching. In spite of this infrastructure, storing, indexing, and serving these videos remains adaily engineering challenge that requires increasing efforts on the part of providers and ISPs. In this paper, we explore how the tags attached to videos by users could help improve this infrastructure, and lead to better performance on a global scale. Our analysis shows that tags can be interpreted as markers of a video's geographic diffusion, with some tags strongly linked to well identified geographic areas. Based on our findings, we demonstrate the potential of tags to help predict distribution of a video's views, and present results suggesting that tags canhelp place videos in globally distributed datacenters. We show in particular that even a simplistic approach based on tags can help predict a minimum of 65.9% of a video's views for a majority of videos, and that a simple tag-based placement strategy is able to improve the hit rate of a distributed on-line video service by up to 6.8% globally over a naive random allocation.","PeriodicalId":430893,"journal":{"name":"2016 IEEE International Conference on Cloud Engineering (IC2E)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133145148","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

Towards Audio-Visual Cues for Cloud Infrastructure Monitoring 面向云基础设施监控的视听线索

2016 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2016-04-04 DOI: 10.1109/IC2E.2016.24

David Bermbach, Jacob Eberhardt

引用次数: 1

Reducing Power Consumption in Data Center by Predicting Temperature Distribution and Air Conditioner Efficiency with Machine Learning 利用机器学习预测温度分布和空调效率，降低数据中心能耗

2016 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2016-04-04 DOI: 10.1109/IC2E.2016.39

Yuya Tarutani, Kazuyuki Hashimoto, G. Hasegawa, Yutaka Nakamura, Takumi Tamura, Kazuhiro Matsuda, Morito Matsuoka

引用次数: 14

A Budget Constrained Scheduling Algorithm for Hybrid Cloud Computing Systems Under Data Privacy 数据隐私下混合云计算系统的预算约束调度算法

2016 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2016-04-04 DOI: 10.1109/IC2E.2016.42

Amin Rezaeian, H. Abrishami, S. Abrishami, Mahmoud Naghibzadeh

引用次数: 11

Container and Microservice Driven Design for Cloud Infrastructure DevOps 容器和微服务驱动的云基础设施设计

2016 IEEE International Conference on Cloud Engineering (IC2E) Pub Date : 2016-04-04 DOI: 10.1109/IC2E.2016.26

Hui Kang, Michael V. Le, S. Tao

引用次数: 167