A resource elasticity framework for QoS-aware execution of cloud applications

Cloud infrastructures consisting of heterogeneous resources are increasingly being utilized for hosting large-scale distributed applications from diverse users with discrete needs. The multifarious cloud applications impose varied demands for computational resources along with multitude of performance implications. Successful hosting of cloud applications necessitates service providers to take into account the heterogeneity existing in the behavior of users, applications and system resources while respecting the user’s agreed Quality of Service (QoS) criteria. In this work, we propose a QoS-Aware Resource Elasticity (QRE) framework that allows service providers to make an assessment of the application behavior and develop mechanisms that enable dynamic scalability of cloud resources hosting the application components. Experimental results conducted on the Amazon EC2 cloud clearly demonstrate the effectiveness of our approach while complying with the agreed QoS attributes of users.     

Failure-aware resource provisioning for hybrid Cloud infrastructure

Hybrid Cloud computing is receiving increasing attention in recent days. In order to realize the full potential of the hybrid Cloud platform, an architectural framework for efficiently coupling public and private Clouds is necessary. As resource failures due to the increasing functionality and complexity of hybrid Cloud computing are inevitable, a failure-aware resource provisioning algorithm that is capable of attending to the end-users quality of service (QoS) requirements is paramount. In this paper, we propose a scalable hybrid Cloud infrastructure as well as resource provisioning policies to assure QoS targets of the users. The proposed policies take into account the workload model and the failure correlations to redirect users’ requests to the appropriate Cloud providers. Using real failure traces and a workload model, we evaluate the proposed resource provisioning policies to demonstrate their performance, cost as well as performance–cost efficiency. Simulation results reveal that in a realistic working condition while adopting user estimates for the requests in the provisioning policies, we are able to improve the users’ QoS about 32% in terms of deadline violation rate and 57% in terms of slowdown with a limited cost on a public Cloud.     

混合云中的一个高效协调器

云计算提供了4种部署模型:公有云、私有云、社区云和混合云.通常,一个私有云中可用的资源是有限的,因此云用户不得不从公有云租用资源.这意味着云用户将会产生额外的费用.越来越多的企业选择混合云来部署它们的应用.在混合云中,为了实现用户的利益最大化,必须满足使用资源的费用最小化和用户的QoS,为此为混合云用户提供了一个既能最小化资源费用又能保证满足QoS的资源分配方法.实验结果表明,该算法在保持低操作成本的同时还满足了用户的QoS.     

Capacity planning for IaaS cloud providers offering multiple service classes

Infrastructure as a Service (IaaS) cloud providers typically offer multiple service classes to satisfy users with different requirements and budgets. Cloud providers are faced with the challenge of estimating the minimum resource capacity required to meet Service Level Objectives (SLOs) defined for all service classes. This paper proposes a capacity planning method that is combined with an admission control mechanism to address this challenge. The capacity planning method uses analytical models to estimate the output of a quota-based admission control mechanism and find the minimum capacity required to meet availability SLOs and admission rate targets for all classes. An evaluation using trace-driven simulations shows that our method estimates the best cloud capacity with a mean relative error of 2.5% with respect to the simulation, compared to a 36% relative error achieved by a single-class baseline method that does not consider admission control mechanisms. Moreover, our method exhibited a high SLO fulfillment for both availability and admission rates, and obtained mean CPU utilization over 91%, while the single-class baseline method had values not greater than 78%.     

Cloud service access control system based on ontologies

Cloud service is a new and distinctive business model for service providers. Access control is an emerging and challenging issue in supporting cloud service business. This work proposes a new access control mechanism called cloud service access control (CSAC). The CSAC mechanism considers payment status and service level as the two essential characteristics of cloud service. Ontology is a theoretical foundation for the CSAC mechanism. Inconsistent access control policies are detected by a set of proposed policy conflict analysis rules. Inappropriate user accesses are inhibited by access control policies according the proposed access denying rules. System architecture is designed to support the CSAC mechanism. A case study is provided to demonstrate how CSAC works. Finally, an evaluation is conducted to measure the concept explosion issue in CSAC.     

Cloud computing service composition: A systematic literature review

The increasing tendency of network service users to use cloud computing encourages web service vendors to supply services that have different functional and nonfunctional (quality of service) features and provide them in a service pool. Based on supply and demand rules and because of the exuberant growth of the services that are offered, cloud service brokers face tough competition against each other in providing quality of service enhancements. Such competition leads to a difficult and complicated process to provide simple service selection and composition in supplying composite services in the cloud, which should be considered an NP-hard problem. How to select appropriate services from the service pool, overcome composition restrictions, determine the importance of different quality of service parameters, focus on the dynamic characteristics of the problem, and address rapid changes in the properties of the services and network appear to be among the most important issues that must be investigated and addressed. In this paper, utilizing a systematic literature review, important questions that can be raised about the research performed in addressing the above-mentioned problem have been extracted and put forth. Then, by dividing the research into four main groups based on the problem-solving approaches and identifying the investigated quality of service parameters, intended objectives, and developing environments, beneficial results and statistics are obtained that can contribute to future research.     

Cloud based management and control system for smart communities: A practical case study

In this study, the implementation of cloud based smart community management and control system was undertaken. SmartComunity.in is a flexible platform to manage and control the affairs of a condominium or society with thorough participation, visibility and transparency. Our research is the first attempt to study one such real life system of cloud based control and management in a smart housing community in India. There is a dearth of exploratory studies that explain the diffusion and adoption of cloud computing in different contexts and from a multiple stakeholder perspective. So, the main contribution of our research is to understand the framework of cloud computing based smart community services in India and the emerging cloud computing ecosystems. This research has wide ranging implications on the future of Internet of Things, and can be extended to elderly health and support, energy efficient systems and smart cities.     

基于文化社会认知算法的云服务优化组合研究

QoS感知的云服务优化组合是云计算领域亟需解决的问题。针对该问题,首先对社会认知算法进行了改进,然后将改进的社会认知算法纳入文化算法的框架之内,构造了新颖的文化社会认知算法,并采用该算法解决QoS感知的云服务优化组合问题。实验结果表明,文化社会认知算法在求解云服务优化组合问题时具有较强的搜索能力和较快的收敛速度;同时,该算法具有很强的推广性,可以用来求解其他类似的组合优化问题。     

基于智能网络与虚拟化计算的移动办公系统信息安全的研究与应用简

本文基于政府行业3G网络和云计算环境移动办公系统的应用实例,重点讨论了构建以网络通信、区域边界、云计算环境、安全管控中心为基础的信息安全平台,为移动办公系统提供一个安全稳定的可信可控可管的移动应用环境的可行性,     

Open-source simulators for Cloud computing: Comparative study and challenging issues

Resource scheduling in infrastructure as a service (IaaS) is one of the keys for large-scale Cloud applications. Extensive research on all issues in real environment is extremely difficult because it requires developers to consider network infrastructure and the environment, which may be beyond the control. In addition, the network conditions cannot be controlled or predicted. Performance evaluations of workload models and Cloud provisioning algorithms in a repeatable manner under different configurations are difficult. Therefore, simulators are developed. To understand and apply better the state-of-the-art of Cloud computing simulators, and to improve them, we study four known open-source simulators. They are compared in terms of architecture, modeling elements, simulation process, performance metrics and scalability in performance. Finally, a few challenging issues as future research trends are outlined.     

基于云计算的军事物流平台设计

通过研究云计算的理论技术,结合军事物流的发展现状,设计了基于云计算的军事物流平台的总体架构,提出了平台的技术架构和功能架构,并对平台提供的具体服务分别进行了阐述。最后对云计算技术在军事物流体系中的实际应用提出了展望。     

A semantic interoperability framework for software as a service systems in cloud computing environments

In cloud computing environments in software as a service (SaaS) level, interoperability refers to the ability of SaaS systems on one cloud provider to communicate with SaaS systems on another cloud provider. One of the most important barriers to the adoption of SaaS systems in cloud computing environments is interoperability. A common tactic for enabling interoperability is the use of an interoperability framework or model. During the past few years, in cloud SaaS level, various interoperability frameworks and models have been developed to provide interoperability between systems. The syntactic interoperability of SaaS systems have already been intensively researched. However, not enough consideration has been given to semantic interoperability issues. Achieving semantic interoperability is a challenge within the world of SaaS in cloud computing environments. Therefore, a semantic interoperability framework for SaaS systems in cloud computing environments is needed. We develop a semantic interoperability framework for cloud SaaS systems. The capabilities and value of service oriented architecture for semantic interoperability within cloud SaaS systems have been studied and demonstrated. This paper is accomplished through a number of steps (research methodology). It begins with a study on related works in the literature. Then, problem statement and research objectives are explained. In the next step, semantic interoperability requirements for SaaS systems in cloud computing environments that are needed to support are analyzed. The details of the proposed semantic interoperability framework for SaaS systems in cloud computing environments are presented. It includes the design of the proposed semantic interoperability framework. Finally, the evaluation methods of the semantic interoperability framework are elaborated. In order to evaluate the effectiveness of the proposed semantic interoperability framework for SaaS systems in cloud computing environments, extensive experimentation and statistical analysis have been performed. The experiments and statistical analysis specify that the proposed semantic interoperability framework for cloud SaaS systems is able to establish semantic interoperability between cloud SaaS systems in a more efficient way. It is concluded that using the proposed framework, there is a significant improvement in the effectiveness of semantic interoperability of SaaS systems in cloud computing environments.     

云计算环境下Web服务集成系统的研究

作为云平台提升应用性能的一种重要手段,Web服务集成技术近年来受到了工业界和学术界的广泛关注。从云计算与Web服务集成技术的结合入手,分析设计了基于云计算的系统体系结构,并基于此提出了基于Web Ser-vices的异构数据集成方法和应用集成的总体架构。最后,给出了该系统的相关实现实例。实验表明,该系统架构的应用在降低构建成本的同时大幅提高了系统性能。     

Development of a Hybrid Manufacturing Cloud

Cloud manufacturing is emerging as a novel business paradigm for the manufacturing industry, in which dynamically scalable and virtualised resources are provided as consumable services over the Internet. A handful of cloud manufacturing systems are proposed for different business scenarios, most of which fall into one of three deployment modes, i.e. private cloud, community cloud, and public cloud. One of the challenges in the existing solutions is that few of them are capable of adapting to changes in the business environment. In fact, different companies may have different cloud requirements in different business situations; even a company at different business stages may need different cloud modes. Nevertheless, there is limited support on migrating to different cloud modes in existing solutions. This paper proposes a Hybrid Manufacturing Cloud that allows companies to deploy different cloud modes for their periodic business goals. Three typical cloud modes, i.e. private cloud, community cloud and public cloud are supported in the system. Furthermore, it enables companies to set self-defined access rules for each resource so that unauthorised companies will not have access to the resource. This self-managed mechanism gives companies full control of their businesses and boosts their trust with enhanced privacy protection. A unified ontology is developed to enhance semantic interoperability throughout the whole process of service provision in the clouds. A Cloud Management Engine is developed to manage all the user-defined clouds, in which Semantic Web technologies are used as the main toolkit. The feasibility of this approach is verified through a group of companies, each of which has complex access requirements for their resources. In addition, a use case is carried out between customers and service providers. This way, optimal service is delivered through the proposed system.     

A QoS-driven approach for cloud computing addressing attributes of performance and security

In recent years, cloud computing has been one of the most widely discussed topics in the field of Information Technology. Owing to the popularity of services offered by cloud environments, several critical aspects of security have aroused interest in the academic and industrial world, where there is a concern to provide efficient mechanisms to combat a wide range of threats. As is well known, the application of security techniques and methodologies has a direct influence on the performance of the system, since security and performance are two quantities that are inversely proportional. This means that if the service providers fail to manage their computing infrastructure efficiently, the demand for services may not be met with the quality required by clients, including security and performance requirements, and the computational resources may be used inefficiently. The aim of this paper was to define QoS-driven approaches for cloud environments on the basis of the results of a performance evaluation of a service in which different security mechanisms are employed. These mechanisms impose additional overhead on the performance of the service, and to counter this, an attempt was made to change computational resources dynamically and on-the-fly. On the basis of the results, it could be shown that in a cloud environment, it is possible to maintain the performance of the service even with the overhead imposed by the security mechanisms, through an alteration in the virtualized computational resources. However, this change in the amount of resources had a direct effect on the response variables.     

面向个性化需求的云制造服务可信评价模型

针对传统的云制造服务可信评价模型中存在的可扩展性弱、难以满足个性化需求等问题,提出一种可扩展性强、可以较好地满足个性化需求的可信评价模型.首先构建多层次的、多粒度的云制造服务可信评价框架;然后基于此框架,提出了基于云模型的云制造服务可信评价方法,在该方法中,引入云模型理论,用于统一表征不同类型的评价指标,以及描述用户的...     

云计算中的集群资源模糊聚类划分模型

随着云计算应用的开展,计算机集群的作用越来越重要,但集群中计算机的性能良莠不齐,虽然能互联且能共享资源,但是很有可能因为某些集群内的计算机的性能不均衡或集群性能与并行任务资源需求不匹配而造成任务低效执行的后果。如何把物理集群(普通局域网互联的计算机构成)分为若干个性能均衡的逻辑集群是集群调度的关键。通过对计算机资源的模糊聚类来划分集群中的计算机,引进任务资源需求向量和最低误差容忍向量机制,把物理集群划分为若干个性能均衡或与并行任务资源匹配的逻辑计算机集群,使集群更易管理调度。对物联云运用此算法划分了网关集群、数据库集群和服务集群,验证了本算法,这种划分方法适合云计算应用。     

一种面向云多层应用的费用高效的资源管理方法

由于部署方便、维护简单并且不需要搭建自己的私有机房,云数据中心正成为大多数互联网公司 尤其是初创公司和中小规模公司 部署应用程序的首选。在以基础设施为服务的云环境里,互联网公司可以根据应用程序的需要动态租赁云基础设施,从而节省预算开支,并保证应用性能。然而,在现有的业界实践中,云服务提供商提供的负载均衡和资源伸缩服务只能监控虚拟机的使用状态,并不能监控应用程序的运行状态,因此无法准确根据应用程序的服务需求自适应变换资源规模。同时,现有的文献和实践中,也很少有 研究从云基础设施使用者的角度出发,为使用者节省基础设施租赁费用或高效使用已租赁基础设施。据此提出了一种面向基础设施云环境下多层应用的费用高效的资源管理方法,其在降低用户费用的同时,还能充分利用所花费用提高应用程序性能。通过仿真对所提方法业界实际使用的方法 进行比较,结果表明所提方法不仅能够提高应用程序的服务质量和服务性能,也能较大地降低公司在基础设施租赁方面的费用。     

云和声搜索算法及其在知识服务组合中的应用

云计算环境下的知识服务是知识与服务的融合, 为知识管理、知识创新提供了新的发展方向。针对基于服务质量(QoS)的知识服务组合优化问题, 在云计算平台下实现和声搜索算法的并行化, 提出了云和声搜索算法。将Skyline方法和理想点法融入到云和声搜索算法中, 对云和声搜索算法进行改进, 提高了算法的运行效率, 确保了解的有效性。实验结果表明, 改进云和声搜索算法在求解知识服务组合优化问题上取得了较好的结果, 在解的质量以及算法的性能方面均有较好的表现。     

Analysis and Provision of QoS for Distributed Grid Applications

Grid computing provides the infrastructure necessary to access and use distributed resources as part of virtual organizations. When used in this way, Grid computing makes it possible for users to participate in collaborative and distributed applications such as tele-immersion, visualization, and computational simulation. Some of these applications operate in a collaborative mode, requiring data to be stored and delivered in a timely manner. This class of applications must adhere to stringent real-time constraints and Quality-of-Service (QoS) requirements. A QoS management approach is therefore required to orchestrate and guarantee the timely interaction between such applications and services. We discuss the design and a prototype implementation of a QoS system, and demonstrate how we enable Grid applications to become QoS compliant. We validate this approach through a case study of an image processing task derived from a nanoscale structures application.