2014 IEEE 7th International Conference on Cloud Computing最新文献_第5页

Incentive-Compatible Online Mechanisms for Resource Provisioning and Allocation in Clouds 云中资源供应和分配的激励兼容在线机制

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.50

Lena Mashayekhy, Mahyar Movahed Nejad, Daniel Grosu, A. Vasilakos

{"title":"Incentive-Compatible Online Mechanisms for Resource Provisioning and Allocation in Clouds","authors":"Lena Mashayekhy, Mahyar Movahed Nejad, Daniel Grosu, A. Vasilakos","doi":"10.1109/CLOUD.2014.50","DOIUrl":"https://doi.org/10.1109/CLOUD.2014.50","url":null,"abstract":"Cloud providers provision their various resources such as CPUs, memory, and storage in the form of Virtual Machine (VM) instances which are then allocated to the users. We design online mechanisms for VM provisioning and allocation in clouds that consider several types of available resources. Our proposed online mechanisms make no assumptions about future demand of VMs, which is the case in real cloud settings. The proposed mechanisms are invoked as soon as a user places a request or some of the allocated resources are released and become available. The mechanisms allocate VM instances to selected users for the period they are requested for, and ensure that the users will continue using their VM instances for the entire requested period. In addition, the mechanisms determine the payment the users have to pay for using the allocated resources. We prove that the mechanisms are incentive-compatible, that is, they give incentives to the users to reveal their true valuations for their requested bundles of VM instances. We investigate the performance of our proposed mechanisms through extensive experiments.","PeriodicalId":288542,"journal":{"name":"2014 IEEE 7th International Conference on Cloud Computing","volume":"40 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":"133354527","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: 41

Performance Variations in Resource Scaling for MapReduce Applications on Private and Public Clouds 私有云和公有云上MapReduce应用的资源伸缩性能变化

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.68

Fan Zhang, M. Sakr

{"title":"Performance Variations in Resource Scaling for MapReduce Applications on Private and Public Clouds","authors":"Fan Zhang, M. Sakr","doi":"10.1109/CLOUD.2014.68","DOIUrl":"https://doi.org/10.1109/CLOUD.2014.68","url":null,"abstract":"In this paper, we delineate the causes of performance variations when scaling provisioned virtual resources for a variety of MapReduce applications. Hadoop MapReduce facilitates the development and execution processes of large-scale batch applications on big data. However, provisioning suitable resources to achieve desired performance at an affordable cost requires expertise into the execution model of MapReduce, the resources available for provisioning and the execution behavior of the application at hand. As an initial step towards automating this process, we characterize the difference in execution response for different MapReduce applications while varying the number of virtualized CPUs and memory resources, number of map slots as well as cluster size on a private cloud. This characterization helps illustrate the performance variation, 5x compared to 36x speedup, of Reduce-intensive and Map-intensive applications at effectively utilizing provisioned resources at different scales (1-64 VMs). By comparing the scalability efficiency, we clearly indicate the under-provisioning or over-provisioning of resources for different MapReduce applications at large scale.","PeriodicalId":288542,"journal":{"name":"2014 IEEE 7th International Conference on Cloud Computing","volume":"14 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":"132051286","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

WinWizard: Expanding Xen with a LibVMI Intrusion Detection Tool WinWizard:用LibVMI入侵检测工具扩展Xen

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.117

Jereme Lamps, I. Palmer, Read Sprabery

{"title":"WinWizard: Expanding Xen with a LibVMI Intrusion Detection Tool","authors":"Jereme Lamps, I. Palmer, Read Sprabery","doi":"10.1109/CLOUD.2014.117","DOIUrl":"https://doi.org/10.1109/CLOUD.2014.117","url":null,"abstract":"Virtual machine introspection (VMI) has grown into a number of novel security measures in recent years. Virtualized environments provide isolation, which gives way to better security. This paper presents an extension, WinWizard, of LibVMI that creates a VMI-based intrusion detection system (IDS) with emphasis on memory introspection. WinWizard is able to detect rootkits that attempts to hide processes from the administrator. Rootkits are able to subvert traditional virus scanning services because they are able to run at the kernel level. Rootkit detection becomes difficult because if the operating system has been subverted, especially at the kernel level, then it is difficult to find unauthorized changes to itself or its components. Most anti-viruses and other rootkit detectors that work on infected systems are usually only effective against rookits that have a defect in their hiding techniques. Rootkit detection through VMI is one way to effectively detect rookits. VMI detection tools will also be useful in industry. Industry is beginning to advance in its usage of cloud based workspaces. Examples of companies include Amazons Workspaces and Citrix XenDesktop. They offer remote desktops for small and medium sized businesses. These workspaces offer a fully managed cloud-based desktop experience where users can access their work resources from a variety of devices. Many universities and small businesses use services like these to reduce the number of IT staff and ease administration of a large number of desktops. As this field becomes more accessible, rootkits are going to drastically affect the performance and security of not only one users desktop, but on entire cloud infrastructures. The main way to detect a rootkit inside of these workspaces would be through virtual machine introspection. WinWinzard has demonstrated to be successful in detecting these types of rootkits, while causing little additional overhead to other virtual machines being hosted on the same hypervisor.","PeriodicalId":288542,"journal":{"name":"2014 IEEE 7th International Conference on Cloud Computing","volume":"71 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":"122358900","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: 13

iOverbook: Intelligent Resource-Overbooking to Support Soft Real-Time Applications in the Cloud iOverbook:智能资源超预定，支持云中的软实时应用

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.78

Faruk Caglar, A. Gokhale

{"title":"iOverbook: Intelligent Resource-Overbooking to Support Soft Real-Time Applications in the Cloud","authors":"Faruk Caglar, A. Gokhale","doi":"10.1109/CLOUD.2014.78","DOIUrl":"https://doi.org/10.1109/CLOUD.2014.78","url":null,"abstract":"Cloud service providers (CSPs) often overbook their resources with user applications despite having to maintain service-level agreements with their customers. Overbooking is attractive to CSPs because it helps to reduce power consumption in the data center by packing more user jobs in less number of resources while improving their profits. Overbooking becomes feasible because user applications tend to overestimate their resource requirements utilizing only a fraction of the allocated resources. Arbitrary resource overbooking ratios, however, may be detrimental to soft real-time applications, such as airline reservations or Netflix video streaming, which are increasingly hosted in the cloud. The changing dynamics of the cloud preclude an offline determination of overbooking ratios. To address these concerns, this paper presents iOverbook, which uses a machine learning approach to make systematic and online determination of overbooking ratios such that the quality of service needs of soft real-time systems can be met while still benefiting from overbooking. Specifically, iOverbook utilizes historic data of tasks and host machines in the cloud to extract their resource usage patterns and predict future resource usage along with the expected mean performance of host machines. To evaluate our approach, we have used a large usage trace made available by Google of one of its production data centers. In the context of the traces, our experiments show that iOverbook can help CSPs improve their resource utilization by an average of 12.5% and save 32% power in the data center.","PeriodicalId":288542,"journal":{"name":"2014 IEEE 7th International Conference on Cloud Computing","volume":"40 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":"121368828","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: 62

Data Centre Optimisation Enhanced by Software Defined Networking 通过软件定义网络增强数据中心优化

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.28

T. Cucinotta, D. Lugones, D. Cherubini, E. Jul

引用次数: 10

A Security PaaS Container with a Customized JVM 带有自定义JVM的安全PaaS容器

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.142

Rongheng Lin, Budan Wu, Sen Su, Peng Xu, Shasha Yang, Yao Zhao

引用次数: 2

User-Controlled Identity Provisioning for Secure Account Sharing 安全帐号共享的用户控制身份发放

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.91

Dongxi Liu, J. Zic

引用次数: 2

Secure Multiparty Data Sharing in the Cloud Using Hardware-Based TPM Devices 使用基于硬件的TPM设备实现云中的安全多方数据共享

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.39

Danan Thilakanathan, Shiping Chen, S. Nepal, R. Calvo, Dongxi Liu, J. Zic

{"title":"Secure Multiparty Data Sharing in the Cloud Using Hardware-Based TPM Devices","authors":"Danan Thilakanathan, Shiping Chen, S. Nepal, R. Calvo, Dongxi Liu, J. Zic","doi":"10.1109/CLOUD.2014.39","DOIUrl":"https://doi.org/10.1109/CLOUD.2014.39","url":null,"abstract":"The trend towards Cloud computing infrastructure has increased the need for new methods that allow data owners to share their data with others securely taking into account the needs of multiple stakeholders. The data owner should be able to share confidential data while delegating much of the burden of access control management to the Cloud and trusted enterprises. The lack of such methods to enhance privacy and security may hinder the growth of cloud computing. In particular, there is a growing need to better manage security keys of data shared in the Cloud. BYOD provides a first step to enabling secure and efficient key management, however, the data owner cannot guarantee that the data consumers device itself is secure. Furthermore, in current methods the data owner cannot revoke a particular data consumer or group efficiently. In this paper, we address these issues by incorporating a hardware-based Trusted Platform Module (TPM) mechanism called the Trusted Extension Device (TED) together with our security model and protocol to allow stronger privacy of data compared to software-based security protocols. We demonstrate the concept of using TED for stronger protection and management of cryptographic keys and how our secure data sharing protocol will allow a data owner (e.g, author) to securely store data via untrusted Cloud services. Our work prevents keys to be stolen by outsiders and/or dishonest authorised consumers, thus making it particularly attractive to be implemented in a real-world scenario.","PeriodicalId":288542,"journal":{"name":"2014 IEEE 7th International Conference on Cloud Computing","volume":"21 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":"125088176","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: 21

RLC - A Reliable Approach to Fast and Efficient Live Migration of Virtual Machines in the Clouds RLC -一种可靠的方法来快速和有效地实时迁移云中的虚拟机

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.56

Sanidhya Kashyap, J. Dhillon, Suresh Purini

{"title":"RLC - A Reliable Approach to Fast and Efficient Live Migration of Virtual Machines in the Clouds","authors":"Sanidhya Kashyap, J. Dhillon, Suresh Purini","doi":"10.1109/CLOUD.2014.56","DOIUrl":"https://doi.org/10.1109/CLOUD.2014.56","url":null,"abstract":"Today, IaaS cloud providers are dynamically minimizing the cost of data centers operations, while maintaining the Service Level Agreement (SLA). Currently, this is achieved by the live migration capability, which is an advanced state-of-the-art technology of Virtualization. However, existing migration techniques suffer from high network bandwidth utilization, large network data transfer, large migration time as well as the destination's VM failure during migration. In this paper, we propose Reliable Lazy Copy (RLC) - a fast, efficient and a reliable migration technique. RLC provides a reasonable solution for high-efficiency and less disruptive migration scheme by utilizing the three phases of the process migration. For effective network bandwidth utilization and reducing the total migration time, we introduce a learning phase to estimate the writable working set (WWS) prior to the migration, resulting in an almost single time transfer of the pages. Our approach decreases the total data transfer by 1.16 x - 12.21x and the total migration time by a factor of 1.42x - 9.84x against the existing approaches, thus providing a fast and an efficient, reliable VM migration of the VMs in the cloud.","PeriodicalId":288542,"journal":{"name":"2014 IEEE 7th International Conference on Cloud Computing","volume":"16 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":"131580582","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

Non-intrusive Critical System Event Recognition and Prediction in Cloud 云环境下非侵入式关键系统事件识别与预测

2014 IEEE 7th International Conference on Cloud Computing Pub Date : 2014-06-27 DOI: 10.1109/CLOUD.2014.93

Yuanyao Liu, Zhengping Wu

引用次数: 5