A method for trust management in cloud computing: Data coloring by cloud watermarking

With the development of Internet technology and human computing, the computing environment has changed dramatically over the last three decades. Cloud computing emerges as a paradigm of Internet computing in which dynamical, scalable and often virtualized resources are provided as services. With virtualization technology, cloud computing offers diverse services (such as virtual computing, virtual storage, virtual bandwidth, etc.) for the public by means of multi-tenancy mode. Although users are enjoying the capabilities of super-computing and mass storage supplied by cloud computing, cloud security still remains as a hot spot problem, which is in essence the trust management between data owners and storage service providers. In this paper, we propose a data coloring method based on cloud watermarking to recognize and ensure mutual reputations. The experimental results show that the robustness of reverse cloud generator can guarantee users embedded social reputation identifications. Hence, our work provides a reference solution to the critical problem of cloud security.     

Defense schemes for variants of distributed denial-of-service (DDoS) attacks in cloud computing: A survey

Cloud computing is a fast-growing and promising technology segment that aims to reduce maintenance and management costs by shifting high-quality computing infrastructure to the Internet. It is emerging as a dominant technology because it provides an on-demand, self-service, scalable, and pay-per-use business model. Despite its numerous benefits, it suffers from several security challenges. As a consequence of on-demand service, availability of computing resources is the crucial attribute of cloud computing among security necessities. In this work, a survey is presented on various issues related to the availability of resources in a cloud environment. Ensuring availability and security of computing/storage resources are still challenging tasks. The adversary class readily exploits the vulnerabilities in the cloud infrastructure for attack implementation. The article presents a study of various categories of distributed denial-of-service (DDoS) attacks in cloud computing and their defense mechanisms. It is believed that this is the first work which surveys all varieties of DDoS attacks in the cloud environment.     

BlobSeer: Next-generation data management for large scale infrastructures

As data volumes increase at a high speed in more and more application fields of science, engineering, information services, etc., the challenges posed by data-intensive computing gain increasing importance. The emergence of highly scalable infrastructures, e.g. for cloud computing and for petascale computing and beyond, introduces additional issues for which scalable data management becomes an immediate need. This paper makes several contributions. First, it proposes a set of principles for designing highly scalable distributed storage systems that are optimized for heavy data access concurrency. In particular, we highlight the potentially large benefits of using versioning in this context. Second, based on these principles, we propose a set of versioning algorithms, both for data and metadata, that enable a high throughput under concurrency. Finally, we implement and evaluate these algorithms in the BlobSeer prototype, that we integrate as a storage backend in the Hadoop MapReduce framework. We perform extensive microbenchmarks as well as experiments with real MapReduce applications: they demonstrate that applying the principles defended in our approach brings substantial benefits to data intensive applications.     

From cloud computing to cloud manufacturing

Cloud computing is changing the way industries and enterprises do their businesses in that dynamically scalable and virtualized resources are provided as a service over the Internet. This model creates a brand new opportunity for enterprises. In this paper, some of the essential features of cloud computing are briefly discussed with regard to the end-users, enterprises that use the cloud as a platform, and cloud providers themselves. Cloud computing is emerging as one of the major enablers for the manufacturing industry; it can transform the traditional manufacturing business model, help it to align product innovation with business strategy, and create intelligent factory networks that encourage effective collaboration. Two types of cloud computing adoptions in the manufacturing sector have been suggested, manufacturing with direct adoption of cloud computing technologies and cloud manufacturing—the manufacturing version of cloud computing. Cloud computing has been in some of key areas of manufacturing such as IT, pay-as-you-go business models, production scaling up and down per demand, and flexibility in deploying and customizing solutions. In cloud manufacturing, distributed resources are encapsulated into cloud services and managed in a centralized way. Clients can use cloud services according to their requirements. Cloud users can request services ranging from product design, manufacturing, testing, management, and all other stages of a product life cycle.     

DaaS: Cloud-based mobile Web service discovery

The proliferation of smartphones and the recent advancement in ubiquitous wireless access have made mobile Web services more possible than ever before. However, finding relevant Web services that can match requests and fit user context remains a major concern. The challenges facing Web service discovery are further magnified by the stringent constraints of mobile devices and the inherit complexity of wireless heterogeneous networks. Cloud computing, with its flexible design and theoretically unlimited computing resources, is a viable approach to bootstrapping Web service discovery. The cloud can build bridges between mobile devices, as a convenient ubiquitous interface, and a backbone infrastructure with abundant computing resources. This paper introduces “Discovery as a service (Daas)”, a novel cloud-based discovery framework that addresses the core components of mobile Web service discovery. The DaaS framework lays the foundation of efficient mobile Web service discovery that takes into consideration user preferences and context. The experimental validation and performance evaluation demonstrate that DaaS can effectively rank relevant services according to the various user context and preferences, in addition to enhancing the precision of the discovered services. The prototype also shows that Web service clustering for discovery significantly improves the overall response time, while the cloud maintains scalability according to prespecified performance criteria.     

A secure re‐encryption scheme for data services in a cloud computing environment

Cloud computing as a promising technology and paradigm can provide various data services, such as data sharing and distribution, which allows users to derive benefits without the need for deep knowledge about them. However, the popular cloud data services also bring forth many new data security and privacy challenges. Cloud service provider untrusted, outsourced data security, hence collusion attacks from cloud service providers and data users become extremely challenging issues. To resolve these issues, we design the basic parts of secure re‐encryption scheme for data services in a cloud computing environment, and further propose an efficient and secure re‐encryption algorithm based on the EIGamal algorithm, to satisfy basic security requirements. The proposed scheme not only makes full use of the powerful processing ability of cloud computing but also can effectively ensure cloud data security. Extensive analysis shows that our proposed scheme is highly efficient and provably secure under existing security model. Copyright © 2015 John Wiley & Sons, Ltd.     

云计算环境下单点登录模型研究

云环境建设的目的在于将各业务系统中的资源和服务统一管理,为用户提供统一的资源和服务接口,而云中的资源和服务分散在各业务系统中管理,为了保证云环境中资源和服务的安全性,以及为了方便用户使用云环境下的资源和服务,就需要进行单点登录模型的设计,通过用户的单点验证,避免用户需要多次验证以使用不同业务系统的资源和服务。本文在分析云计算单点登录需求的基础上,进行单点登录模型整体结构和单点登录流程的设计。     

空间云计算

在21世纪数据、计算、并发访问以及时空都密集的情况下,地理信息科学面临着大量信息技术的挑战。这些挑战要求计算基础设施做好充足的准备。云计算提供了灵活的、按需计算的平台来整合观测系统、参数提取算法、现象模拟、分析可视化和决策支持,同时它的社会影响和用户反馈正是地理信息科学的必备要素。通过给出我们关于云计算如何支持地理信息科学,以及时空原理这个地理信息科学的核心如何利用云计算所带来的好处这两个方面的调查,我们讨论了云计算在地理信息科学上的应用。     

Contract RBAC in cloud computing

Cloud computing is a fast growing field, which is arguably a new computing paradigm. In cloud computing, computing resources are provided as services over the Internet and users can access resources based on their payments. The issue of access control is an important security scheme in the cloud computing. In this paper, a Contract RBAC model with continuous services for user to access various source services provided by different providers is proposed. The Contract RBAC model extending from the well-known RBAC model in cloud computing is shown. The extending definitions in the model could increase the ability to meet new challenges. The Contract RBAC model can provide continuous services with more flexible management in security to meet the application requirements including Intra-cross cloud service and Inter-cross cloud service. Finally, the performance analyses between the traditional manner and the scheme are given. Therefore, the proposed Contract RBAC model can achieve more efficient management for cloud computing environments.     

Towards an autonomic performance management approach for a cloud broker environment using a decomposition–coordination based methodology

Efficient resource allocation of computational resources to services is one of the predominant challenges in a cloud computing environment. Furthermore, the advent of cloud brokerage and federated cloud computing systems increases the complexity of cloud resource management. Cloud brokers are considered third party organizations that work as intermediaries between the service providers and the cloud providers. Cloud brokers rent different types of cloud resources from a number of cloud providers and sublet these resources to the requesting service providers. In this paper, an autonomic performance management approach is introduced that provides dynamic resource allocation capabilities for deploying a set of services over a federated cloud computing infrastructure by considering the availability as well as the demand of the cloud computing resources. A distributed control based approach is used for providing autonomic computing features to the proposed framework via a feedback-based control loop. This distributed control based approach is developed using one of the decomposition–coordination methodologies, named interaction balance, for interactive bidding of cloud computing resources. The primary goals of the proposed approach are to maintain the service level agreements, maximize the profit, and minimize the operating cost for the service providers and the cloud broker. The application of interaction balance methodology and prioritization of profit maximization for the cloud broker and the service providers during resource allocation are novel contributions of the proposed approach.     

CyberGuarder: A virtualization security assurance architecture for green cloud computing

As the sizes of IT infrastructure continue to grow, cloud computing is a natural extension of virtualisation technologies that enable scalable management of virtual machines over a plethora of physically connected systems. The so-called virtualisation-based cloud computing paradigm offers a practical approach to green IT/clouds, which emphasise the construction and deployment of scalable, energy-efficient network software applications (NetApp) by virtue of improved utilisation of the underlying resources. The latter is typically achieved through increased sharing of hardware and data in a multi-tenant cloud architecture/environment and, as such, accentuates the critical requirement for enhanced security services as an integrated component of the virtual infrastructure management strategy. This paper analyses the key security challenges faced by contemporary green cloud computing environments, and proposes a virtualisation security assurance architecture, CyberGuarder, which is designed to address several key security problems within the ‘green’ cloud computing context. In particular, CyberGuarder provides three different kinds of services; namely, a virtual machine security service, a virtual network security service and a policy based trust management service. Specifically, the proposed virtual machine security service incorporates a number of new techniques which include (1) a VMM-based integrity measurement approach for NetApp trusted loading, (2) a multi-granularity NetApp isolation mechanism to enable OS user isolation, and (3) a dynamic approach to virtual machine and network isolation for multiple NetApp’s based on energy-efficiency and security requirements. Secondly, a virtual network security service has been developed successfully to provide an adaptive virtual security appliance deployment in a NetApp execution environment, whereby traditional security services such as IDS and firewalls can be encapsulated as VM images and deployed over a virtual security network in accordance with the practical configuration of the virtualised infrastructure. Thirdly, a security service providing policy based trust management is proposed to facilitate access control to the resources pool and a trust federation mechanism to support/optimise task privacy and cost requirements across multiple resource pools. Preliminary studies of these services have been carried out on our iVIC platform, with promising results. As part of our ongoing research in large-scale, energy-efficient/green cloud computing, we are currently developing a virtual laboratory for our campus courses using the virtualisation infrastructure of iVIC, which incorporates the important results and experience of CyberGuarder in a practical context.     

云计算环境下资源调度系统设计与实现

在云计算环境下,对开放的网络大数据库信息系统中的数据进行优化调度,提高数据资源的利用效率和配置优化能力;传统的资源调度算法采用资源信息的自相关匹配方法进行资源调度,当数据传输信道中的干扰较大及资源信息流的先验数据缺乏时,资源调度的均衡性不好,准确配准度不高;提出一种基于云计算资源负载均衡控制和信道自适应均衡的资源调度算法,并进行调度系统的软件开发和设计;首先构建了云计算环境下开放网络大数据库信息资源流的时间序列分析模型,采用自适应级联滤波算法对拟合的资源信息流进行滤波降噪预处理,提取滤波输出的资源信息流的关联维特征,通过资源负载均衡控制和信道自适应均衡算法实现资源调度改进;仿真结果表明,采用资源调度算法进行资源调度系统的软件设计,提高了资源调度的信息配准能力和抗干扰能力,计算开销较小,技术指标具有优越性。     

Multi-tenant Verification-as-a-Service (VaaS) in a cloud

Formal methods and verification technique are often used to develop mission-critical systems. Cloud computing offers new computation models for applications and the new model can be used for formal verification. But formal verification tools and techniques may need to be updated to exploit the cloud architectures. Multi-Tenant Architecture (MTA) is a design architecture used in SaaS (Software-as-a-Service) where a tenant can customize its applications by integrating either services already stored in the SaaS database or newly supplied services. This paper proposes a new concept VaaS (Verification-as-a-Service), similar to SaaS, by leveraging the computing power offered by a cloud environment with automated provisioning, scalability, and service composition. A VaaS hosts verification software in a cloud environment, and these services can be called on demand, and can be composed to verify a software model. This paper presents a VaaS architecture with components, and ways that a VaaS can be used to verify models. Bigragh is selected as the modeling language for illustration as it can model mobile applications. A Bigraph models can be verified by first converting it to a state model, and the state model can be verified by model-checking tools. The VaaS services combination model and execution model are also presented. The algorithm of distributing VaaS services to a cloud is given and its efficiency is evaluated. A case study is used to demonstrate the feasibility of a VaaS.     

网格环境中一种有效的Web服务资源组织机制

Web服务资源的有效组织与获取是网格计算中的关键性问题．基于OGSA(open grid service architecture)框架提出了一种有效的网格Web服务资源组织体系模型，它将Web服务资源的逻辑结构与物理资源组织分开，以层次结构的Web服务解析系统(Web services name system，WSNS)来进行Web服务资源查找与定位，以区域自治系统(area autonomy system，AAS)来进行Web服务资源的维护．详细描述了该模型的实现机制、组织协议与数据结构．通过对模型的分析和对原型系统的模拟表明该模型是合理而有效的：它可以在较小开销下获得较满意的资源组织与定位性能，能适应网格Web服务资源的异构、复杂与动态性、多级的负载平衡和良好的可扩展性．’     

关于云计算的几点思考

云计算是以虚拟化技术为基础,以网络为载体提供基础架构、平台、软件等服务为形式,整合大规模可扩展的计算、存储、数据、应用等分布式计算资源进行协同工作的超级计算模式。云计算技术的出现使得人们可以直接通过网络应用获取软件和计算能力,这一新的模式将会给传统的IT产业带来一场巨大的变革,云计算正在成为一种发展趋势。本文就云计算的发展前景和存在的风险谈几点思考。     

Modeling urban growth sustainability in the cloud by augmenting Google Earth Engine (GEE)

Google Earth Engine (GEE) has been increasingly used in environmental and urban studies due to its cloud-based geospatial processing capability and accessibility to a large collection of geospatial datasets like Landsat, Modis, etc. However, at present, ecological and urban modeling efforts based on GEE are facing three grave challenges: current illustrations of GEE are to a large extent “straightforward mapping” applications; technical complexities that ecological or urban modelers have to overcome in order to effectively and easily use GEE to develop image processing based environmental models; and the majority of ecological and urban modelers are not aware of new analytical approaches that are becoming available because of the unprecedent geospatial processing capability and large collection of big geospatial datasets GEE has brought to them. The great potential of GEE to support ecological and urban modeling is less explored. In this study, we augmented GEE functions with a few sets of user-customized functions for improving image classification accuracy, estimating ecosystem services, and modeling urban growth sustainability. The paper is the first effort of modeling urban sustainability based on the concept of ecosystem service value (ESV) and in the cloud with GEE; is the first application of classifying GEE Landsat time-series images to compute yearly ESV; and creates the first set of cloud tools to augment GEE for ecologists and urban modelers to model urban sustainability from GEE and ESV. The paper also chose Hohhot City, Inner Mongolia as a case study to model urban sustainability in a time-series 12 years (2005–2016). The case study successfully estimated ecosystem service values and analyzed urban growth sustainability. It also revealed spatial disparities and temporal dynamics of urban growth sustainability in Hohhot City. The study provides an easy-to-adapt illustration on using GEE for image-based ecological and urban modeling.     

利用可信计算技术改善云计算的安全性

云计算影响了互联网上世界上任何地方远程服务器处理、数据存储和共享的方式。这种共享多种分布式资源方式,使得安全问题更加复杂化。本文分析了云计算环境下的安全服务,通过整合可信计算环境来建立云计算系统。可信计算平台模式可以提高云计算的安全性。可信计算模式重要的安全服务包括加密,认证,完整性和保密性等都可以用在云计算系统中。     

Matrix based proactive resource provisioning in mobile cloud environment

Mobile cloud computing is a dynamic, virtually scalable and network based computing environment where mobile device acts as a thin client and applications run on remote cloud servers. Mobile cloud computing resources required by different users depend on their respective personalized applications. Therefore, efficient resource provisioning in mobile clouds is an important aspect that needs special attention in order to make the mobile cloud computing a highly optimized entity. This paper proposes an adaptive model for efficient resource provisioning in mobile clouds by predicting and storing resource usages in a two dimensional matrix termed as resource provisioning matrix. These resource provisioning matrices are further used by an independent authority to predict future required resources using artificial neural network. Independent authority also checks and verifies resource usage bill computed by cloud service provider using resource provisioning matrices. It provides cost computation reliability for mobile customers in mobile cloud environment. Proposed model is implemented on Hadoop using three different applications. Results indicate that proposed model provides better mobile cloud resources utilization as well as maintains quality of service for mobile customer. Proposed model increases battery life of mobile device and decreases data usage cost for mobile customer.     

Cloud computing adoption: an empirical study of customer preferences among start-up companies

Cloud computing represents a paradigm shift to utmost scalable and flexible IT services. However, research related to preferences of certain customers concerning cloud services is scarce. Especially start-up companies with their limited capacities to implement and operate IT infrastructure and their great demand for scalable and affordable IT resources are predestined as customers of cloud based services. In this study, we apply a multi-method approach to investigate customer preferences among start-up companies. Based on a literature review and a market analysis of cloud service models, we propose a set of cloud provider characteristics. These properties were examined among 108 start-up companies and analyzed in three steps using factor analysis to define customer preferences, cluster analysis to identify customer segments and discriminant analysis to validate the identified clusters. The results show that start-ups can be basically divided in five clusters each with certain requirements on cloud provider characteristics.