2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom)最新文献

Simulating High Availability Scenarios in Cloud Data Centers: A Closer Look 模拟云数据中心中的高可用性场景:深入研究

2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2015-11-30 DOI: 10.1109/CloudCom.2015.62

Mohamed Abu Sharkh, A. Shami, P. Ohlen, Abdelkader H. Ouda, A. Kanso

{"title":"Simulating High Availability Scenarios in Cloud Data Centers: A Closer Look","authors":"Mohamed Abu Sharkh, A. Shami, P. Ohlen, Abdelkader H. Ouda, A. Kanso","doi":"10.1109/CloudCom.2015.62","DOIUrl":"https://doi.org/10.1109/CloudCom.2015.62","url":null,"abstract":"Migrating to the cloud is becoming a necessity for the majority of businesses. Cloud tenants require certain levels of performance in aspects like high availability and service rate and deployment options. On the other hand, Cloud providers are in constant pursuit of a system that satisfies client demands for resources, maximizes availability, minimizes power consumption and, in turn, minimizes the cloud providers' cost. A main challenge cloud providers face here is ensuring high availability (HA). High availability includes the combined reliability of components of all categories including network, computational, hardware and software components of all layers. In this work, we first address the need for a cloud simulator that enables HA algorithm testing in cloud environments and observe its impact on energy efficiency. We introduce a framework to amend cloud simulators with critical HA features. We take GreenCloud, a major simulator with a direct focus on green computing, and implement these features as an additional measurement layer. We demonstrate these added features by simulating their impact on a phased communication application (PCA).","PeriodicalId":164664,"journal":{"name":"2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123936506","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

StoreSim: Optimizing Information Leakage in Multicloud Storage Services StoreSim:优化多云存储服务中的信息泄漏

2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2015-11-30 DOI: 10.1109/CloudCom.2015.26

Hao Zhuang, Rameez Rahman, P. Hui, K. Aberer

{"title":"StoreSim: Optimizing Information Leakage in Multicloud Storage Services","authors":"Hao Zhuang, Rameez Rahman, P. Hui, K. Aberer","doi":"10.1109/CloudCom.2015.26","DOIUrl":"https://doi.org/10.1109/CloudCom.2015.26","url":null,"abstract":"Many schemes have been recently advanced for storing data on multiple clouds. Distributing data over different cloud storage providers (CSPs) automatically provides users with a certain degree of information leakage control, as no single point of attack can leak all user's information. However, unplanned distribution of data chunks can lead to high information disclosure even while using multiple clouds. In this paper, to address this problem we present StoreSim, an information leakage aware storage system in multicloud. StoreSim aims to store syntactically similar data on the same cloud, thus minimizing the user's information leakage across multiple clouds. We design an approximate algorithm to efficiently generate similarity-preserving signatures for data chunks based on MinHash and Bloom filter, and also design a function to compute the information leakage based on these signatures. Next, we present an effective storage plan generation algorithm based on clustering for distributing data chunks with minimal information leakage across multiple clouds. Finally, we evaluate our scheme using two real datasets from Wikipedia and GitHub. We show that our scheme can reduce the information leakage by up to 60% compared to unplanned placement.","PeriodicalId":164664,"journal":{"name":"2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128161333","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

Dynamic Pricing Scheme: Towards Cloud Revenue Maximization 动态定价方案:走向云收益最大化

2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2015-11-30 DOI: 10.1109/CloudCom.2015.14

Fadi Alzhouri, A. Agarwal

引用次数: 10

DCRA: Decentralized Cognitive Resource Allocation Model for Game as a Service 游戏即服务的分散认知资源分配模型

2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2015-11-30 DOI: 10.1109/CloudCom.2015.63

Nabil M. Al-Rousan, Wei Cai, Hong Ji, Victor C. M. Leung

{"title":"DCRA: Decentralized Cognitive Resource Allocation Model for Game as a Service","authors":"Nabil M. Al-Rousan, Wei Cai, Hong Ji, Victor C. M. Leung","doi":"10.1109/CloudCom.2015.63","DOIUrl":"https://doi.org/10.1109/CloudCom.2015.63","url":null,"abstract":"Game as a Service (GaaS) has rapidly emerged to the industry of cloud gaming. The power of GaaS lies on having one source of code with multiple users. Several systems were proposed to model GaaS. However, none has built a scalable and reliable model for such a service. The importance of having such a model lies on having an Internet-scale platform able to provide flexibility of different types of games genre and lower the barrier of end systems (i.e. mobile clients) while taking into consideration the probability of excessive loads and failures. In this paper, we implement a Distributed Cognitive Resource Allocation (DCRA) model to run mobile games on a large-scale distributed system. On the contrary of the existing centralized models, DCRA scales with the increase of mobile clients to handle high concurrent loads of clients' requests while providing a stable level of gaming experience. The results show that DCRA is able to scale well by providing almost fixed throughput and delay while increasing the clients requests load. Also, the system preserve its key features while simulating failures.","PeriodicalId":164664,"journal":{"name":"2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132740644","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

Security-as-a-Service for Microservices-Based Cloud Applications 基于微服务的云应用的安全即服务

2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2015-11-30 DOI: 10.1109/CloudCom.2015.93

Yuqiong Sun, Susanta Nanda, T. Jaeger

{"title":"Security-as-a-Service for Microservices-Based Cloud Applications","authors":"Yuqiong Sun, Susanta Nanda, T. Jaeger","doi":"10.1109/CloudCom.2015.93","DOIUrl":"https://doi.org/10.1109/CloudCom.2015.93","url":null,"abstract":"Microservice architecture allows different parts of an application to be developed, deployed and scaled independently, therefore becoming a trend for developing cloud applications. However, it comes with challenging security issues. First, the network complexity introduced by the large number of microservices greatly increases the difficulty in monitoring the security of the entire application. Second, microservices are often designed to completely trust each other, therefore compromise of a single microservice may bring down the entire application. The problems are only exacerbated by the cloud, since applications no longer have complete control over their networks. In this paper, we propose a design for security-as-a-service for microservices-based cloud applications. By adding a new API primitive FlowTap for the network hypervisor, we build a flexible monitoring and policy enforcement infrastructure for network traffic to secure cloud applications. We demonstrate the effectiveness of our solution by deploying the Bro network monitor using FlowTap. Results show that our solution is flexible enough to support various kinds of monitoring scenarios and policies and it incurs minimal overhead (~6%) for real world usage. As a result, cloud applications can leverage our solution to deploy network security monitors to flexibly detect and block threats both external and internal to their network.","PeriodicalId":164664,"journal":{"name":"2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133826422","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: 77

The Ignite Distributed Collaborative Scientific Visualization System Ignite分布式协同科学可视化系统

2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2015-11-30 DOI: 10.1007/978-3-319-33769-2_19

Sushil Bhojwani, Matt Hemmings, D. Ingalls, Jens Lincke, R. Krahn, David John Lary, P. McGeer, Glenn Ricart, Marko Röder, Y. Coady, U. Stege

引用次数: 9

Data Velocity Scaling via Dynamic Monitoring Frequency on Ultrascale Infrastructures 基于超大规模基础设施动态监测频率的数据速度扩展

2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2015-11-30 DOI: 10.1109/CloudCom.2015.66

Toni Mastelić, I. Brandić

{"title":"Data Velocity Scaling via Dynamic Monitoring Frequency on Ultrascale Infrastructures","authors":"Toni Mastelić, I. Brandić","doi":"10.1109/CloudCom.2015.66","DOIUrl":"https://doi.org/10.1109/CloudCom.2015.66","url":null,"abstract":"Monitoring ultrascale systems such as Clouds requires collecting enormous amount of data by periodically reading metric values from a system. Current approaches tend to select a static frequency for sampling monitoring data. On one hand, over-sampling the data by collecting it at high frequencies results in data redundancy during steady runs of the system. On the other hand, under-sampling with low monitoring frequencies results in information loss during volatile behaviour of the system as data is significantly diluted. Therefore, choosing an optimal monitoring frequency represents a challenging research issue. In this paper, we propose a dynamic monitoring frequency algorithm for collecting monitoring data from ultrascale systems such as Clouds. The algorithm deterministically reduces data velocity by self-adapting the monitoring frequency to the volatility of data being collected. Consequently, it collects less data due to fewer readings, while keeping the same data value as the equivalent static monitoring frequency. The proposed approach is evaluated using Google traces where it is able to reduce the velocity of monitoring data by up to 85% without diluting information quality.","PeriodicalId":164664,"journal":{"name":"2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124754578","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

Virtualized FPGA Accelerators for Efficient Cloud Computing 面向高效云计算的虚拟化FPGA加速器

2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2015-11-30 DOI: 10.1109/CloudCom.2015.60

Suhaib A. Fahmy, Kizheppatt Vipin, Shanker Shreejith

引用次数: 144

A Productive Cloud Computing Platform Research for Big Data Analytics 面向大数据分析的高效云计算平台研究

2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2015-11-30 DOI: 10.1109/CloudCom.2015.113

Yuzhong Yan, Chao Chen, Lei Huang

引用次数: 5

An Empirical Study for Evaluating the Performance of jclouds jclouds性能评价的实证研究

2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom) Pub Date : 2015-11-30 DOI: 10.1109/CloudCom.2015.61

M. A. C. Ismael, César Alberto da Silva, Gabriel Costa Silva, R. Ré

引用次数: 4