Development of a Cloud Trust Label: A Delphi Approach

The purpose of this research is to identify the potential information components of an online, real-time trust label, which is proposed as a communication mechanism to encourage trust in cloud service providers and cloud computing products. An online Delphi process was used with 28 cloud computing experts (including vendors, software providers, and legal and business representatives). The proposed label contains 81 information components, covering the cloud service provider (e.g. physical location, legal jurisdiction), the cloud service itself (e.g. data location, security, backup, certification), and a historical service-level summary (e.g. uptime data, support response times). The potential benefits of such a label to encourage trustworthiness perceptions and trust behaviors in the cloud computing environment are explored. Limitations of the study are highlighted, and further research studies are suggested to test the concept of the label and to refine the components of the label itself.     

Platform as a service gateway for the Fog of Things

Internet of Things (IoT), one of the key research topics in recent years, together with concepts from Fog Computing, brings rapid advancements in Smart City, Monitoring Systems, industrial control, transportation and other fields. These applications require a reconfigurable sensor architecture that can span multiple scenarios, devices and use cases that allow storage, networking and computational resources to be efficiently used on the edge of the network. There are a number of platforms and gateway architectures that have been proposed to manage these components and enable application deployment. These approaches lack horizontal integration between multiple providers as well as higher order functionalities like load balancing and clustering. This is partly due to the strongly coupled nature of the deployed applications, a lack of abstraction of device communication layers as well as a lock-in for communication protocols. This limitation is a major obstacle for the development of a protocol agnostic application environment that allows for single application to be migrated and to work with multiple peripheral devices with varying protocols from different local gateways. This research looks at existing platforms and their shortcomings as well as proposes a messaging based modular gateway platform that enables clustering of gateways and the abstraction of peripheral communication protocol details. These novelties allow applications to send and receive messages regardless of their deployment location and destination device protocol, creating a more uniform development environment. Furthermore, it results in a more streamlined application development and testing while providing more efficient use of the gateway’s resources. Our evaluation of a prototype for the system shows the need for the migration of resources and the QoS advantages of such a system. The examined use case scenarios show that clustering proves to be an advantage in certain use cases as well as presenting the deployment of a larger testing and control environment through the platform.     

Zero knowledge based client side deduplication for encrypted files of secure cloud storage in smart cities

As typical applications in the field of the cloud computing, cloud storage services are popular in the development of smart cities for their low costs and huge storage capacity. Proofs-of-ownership (PoW) is an important cryptographic primitive in cloud storage to ensure that a client holds the whole file rather than part of it in secure client side data deduplication. The previous PoW schemes worked well when the file is in plaintext. However, the privacy of the clients’ data may be vulnerable to honest-but-curious attacks. To deal with this issue, the clients tend to encrypt files before outsourcing them to the cloud, which makes the existing PoW schemes inapplicable any more. In this paper, we first propose a secure zero-knowledge based client side deduplication scheme over encrypted files. We prove that the proposed scheme is sound, complete and zero-knowledge. The scheme can achieve a high detection probability of the clients’ misbehavior. Then we introduced a proxy re-encryption based key distribution scheme. This scheme ensures that the server knows nothing about the encryption key even though it acts as a proxy to help distributing the file encryption key. It also enables the clients who have gained the ownership of a file to share the file with the encryption key generated without establishing secure channels among them. It is proved that the clients’ private key cannot be recovered by the server or clients collusion attacks during the key distribution phase. Our performance evaluation shows that the proposed scheme is much more efficient than the existing client side deduplication schemes.     

基于云计算和物联网的网络大数据技术研究

为了使网络大数据应用的范围更广,更大程度地提高网络数据存储与管理精度,减少网络数据处理与控制的时间,需要对网络大数据进行研究。当前的网络大数据研究方法多是采用Hadoop基础架构对网络大数据进行研究,在数据存储中没有设定具体的安全存储指标,无法得到数据安全存储指标权重,存在数据存储安全性能低,网络大数据研究精度偏差大等问题。为此,提出一种基于云计算和物联网的网络大数据研究方法。该方法首先利用分级网络编码对网络数据进行传输,以传输的数据为基础,采用CRC算法实现网络数据的计算,然后依据分组存储的方式将数据进行存储,最后利用分层逆序叠加定位法对网络数据进行高精度查询,由此完成对网络大数据的研究。实验结果表明,所提方法可以全面具体地对网络大数据进行研究,提高了数据处理精度和网络数据计算速度,增加了网络数据存储空间容量和查询效率,减少了网络数据运行时的丢失率,扩展了网络数据的运作范围,为后续网络大数据的研究提供了强有力的依据。     

高校就业服务信息门户系统的设计

就业是社会及其关注的问题,也是高校一项重要的工作。本文设计的高校就业服务信息门户系统的目的是完善高校就业服务工作,将学生、用人单位、就业政策和高校的信息有效的进行结合和对接。本文从技术支持、功能设计、数据库设计和用户界面几方面对系统的设计进行了详细的阐述。     

基于基准测试的高性能计算云研究

随着云计算技术的发展,高性能计算云(HPC in the Cloud)已得到学术界和产业界的关注。由于虚拟化技术带来的性能开销,高性能计算云面临着一些挑战。针对“高性能计算+云”的计算模式,分析了高性能计算云的优势,深入介绍了国内外基于基准测试的高性能计算云的性能评测、性能优化、能耗和成本效益等关键问题,得出了针对基准测试的高性能计算云研究的基本思路,并对当前面临的问题和今后的发展趋势进行了总结和展望。     

基于相空间的云计算仿真系统研究与设计

提出并实现了一种基于热力学相空间的云计算集群仿真系统设计方法。将云计算集群节点信息投影到相空间,构建云计算系统的相空间分析模型,将云计算集群节点的参数变化转变为其在相空间投影点的运动,并通过相空间的宏观热力学参数反映云计算集群的整体状态,为云计算核心调度算法的研究和云计算数据中心的运行测试提供了仿真测试平台和衡量标准。实验结果表明,全新构建的云计算仿真系统的仿真实验环境搭建简单,仿真结果能够直观、全面地反映出云计算集群的整体状态和调度算法性能等。     

并行化的情感分类算法的研究

在海量数据集上执行情感分类任务时,传统的单机情感分类算法的扩展性成为系统的瓶颈.在云计算平台Hadoop上,实现了情感分类任务中特征提取、特征向量加权和情感分类等算法的MapReduce化.在情感语料数据集上,对各种子步骤组合下情感分类算法的精度及每种算法的时间开销进行了对比分析.实验结果验证了实现的并行化情感分类算法的有效性,同时它为用户选择合适算法实现情感分类任务提供了有价值的参考信息.     

基于支点的数据中心网络地址快速自动配置方法研究

目前云计算数据中心规模大,网络设备多,手动配置设备地址不但耗时耗力,而且容易出错。已有自动配置工作未能充分利用数据中心网络拓扑结构特征,导致从规划设计到实际设备配置的映射过程回溯步骤多,效率低。为此,提出了一种基于支点的数据中心网络地址快速自动配置方法PFAC(Pivot-based Fast Automatic Configuration)。PFAC通过预处理分析数据中心网络拓扑层次关系,依据拓扑特征优选支点完成快速匹配,并基于支点缩小配置映射节点的候选集,有效提高了配置效率。基于FatTree结构的模拟实验表明,PFAC能够根据数据中心网络规划蓝图,自动快速地为物理设备分配地址。与经典数据中心网络地址配置方法相比,PFAC算法平均耗时缩短了35%。     

基于Stackelberg领导模式下的云资源定价研究

资源管理是云计算中最重要的一部分。介绍了基于现有云银行模型的云银行生命周期,并提出了合适的定价策略。它根据不同时期云银行的特点得出不同的定价策略。本文的目的是提供一个自动更新机制来定价云资源,从而最大化所有参与者的利益。