DR-Cloud: Multi-Cloud Based Disaster Recovery Service简

With the rapid popularity of cloud computing paradigm, disaster recovery using cloud resources becomes an attractive approach. This paper presents a practical multi-cloud based disaster recovery service model： DR- Cloud. With DR-Cloud, resources of multiple cloud service providers can be utilized cooperatively by the disaster recovery service provider. A simple and unified interface is exposed to the customers of DR-Cloud to adapt the heterogeneity of cloud service providers involved in the disaster recovery service, and the internal processes between clouds are invisible to the customers. DR-Cloud proposes multiple optimization scheduling strategies to balance the disaster recovery objectives, such as high data reliability, low backup cost, and short recovery time, which are also transparent to the customers. Different data scheduling strategies based on DR-Cloud are suitable for different kinds of data disaster recovery scenarios. Experimental results show that the DR-Cloud model can cooperate with cloud service providers with various parameters effectively, while its data scheduling strategies can achieve their optimization objectives efficiently and are widely applicable.     

基于马尔可夫链的体能训练质量评价简

介绍了马尔可夫链理论，探讨了马尔可夫链理论在体能训练质量评价中的应用．通过建模、实例阐述了该应用的方法及步骤，为体能训练质量评价提供了一种较为客观的方法，对于提高体能训练水平具有积极的意义．     

Collaborative Network Security in Multi-Tenant Data Center for Cloud Computing简

A data center is an infrastructure that supports Internet service. Cloud comput the face of the Internet service infrastructure, enabling even small organizations to quickly ng is rapidly changing build Web and mobile applications for millions of users by taking advantage of the scale and flexibility of shared physical infrastructures provided by cloud computing. In this scenario, multiple tenants save their data and applications in shared data centers, blurring the network boundaries between each tenant in the cloud. In addition, different tenants have different security requirements, while different security policies are necessary for different tenants. Network virtualization is used to meet a diverse set of tenant-specific requirements with the underlying physical network enabling multi-tenant datacenters to automatically address a large and diverse set of tenants requirements. In this paper, we propose the system implementation of vCNSMS, a collaborative network security prototype system used n a multi-tenant data center. We demonstrate vCNSMS with a centralized collaborative scheme and deep packet nspection with an open source UTM system. A security level based protection policy is proposed for simplifying the security rule management for vCNSMS. Different security levels have different packet inspection schemes and are enforced with different security plugins. A smart packet verdict scheme is also integrated into vCNSMS for ntelligence flow processing to protect from possible network attacks inside a data center network     

URMG: Enhanced CBMG-Based Method for Automatically Testing Web Applications in the Cloud简

To satisfy the rapid growth of cloud technologies, a large number of web applications have been developed and deployed, and these applications are being run in clouds. Due to the scalability provided by clouds, a single web application may be concurrently visited by several millions or billions of users. Thus, the testing and performance evaluations of these applications are increasingly important. User model based evaluations can significantly reduce the manual work required, and can enable us to determine the performance of applications under real runtime environments. Hence, it has become one of the most popular evaluation methods in both industry and academia. Significant efforts have focused on building different kinds of models using mining web access logs, such as Markov models and Customer Behavior Model Graph （CBMG）. This paper proposes a new kind of model, named the User Representation Model Graph （URMG）, which is built based on CBMG. It uses an algorithm to refine CBMG and optimizes the evaluations execution process. Based on this model, an automatic testing and evaluation system for web applications is designed, implemented, and deployed in our test cloud, which is able to execute all of the analysis and testing operations using only web access logs. In our system, the error rate caused by random access to applications in the execution phase is also reduced, and the results show that the error rate of the evaluation that depends on URMG is 50% less than that which depends on CBMG.     

BPGM: A Big Graph Mining Tool简

The design and implementation of a scalable parallel mining system target for big graph analysis has proven to be challenging. In this study, we propose a parallel data mining system for analyzing big graph data generated on a Bulk Synchronous Parallel （BSP） computing model named BSP-based Parallel Graph Mining （BPGM）. This system has four sets of parallel graph mining algorithms programmed in the BSP parallel model and a well-designed workflow engine optimized for cloud computing to invoke these algorithms. Experimental results show that the graph mining algorithm components in BPGM are efficient and have better performance than big cloud-based parallel data miner and BC-BSP.     

追风人物简

大器晚成的游泳健将连创11项世界纪录 据日本媒体报道．现年99岁的日本老人长冈三重子从95岁起接连创下了95～99岁年龄段的仰泳、自由泳．蛙泳等11项世界纪录。她将于2014年开始进入100～104岁参赛组．挑战新的记录。     

云计算资源分配策略研究

云计算是一种新型的计算模式,已经成为国际上的研究热点。在介绍云计算的相关概念基础上,综述了当前国内外关于云计算资源分配的研究现状,分析云计算资源分配所面临的关键问题,然后进一步指明云计算资源分配算法的研究方向。     

基于云计算的云物流在快递行业中的应用

云物流是吸收了云计算和电子商务平台的基本理念,形成独特的“平台开放,资源共享,服务集成,终端无限”的一种新型商业模式,不同于传统的物流与快递企业商业模式。文章对云物流的概念及特征进行了阐述,进而对云物流应用于快递行业的依据做出详细的解析。     

移动云计算嵌套式两阶段博弈计算卸载算法

移动云计算中,移动设备需要决定哪些应用部分卸载至云端处理,即计算卸载决策问题。针对这一问题,提出了一种嵌套式两阶段博弈算法。第一阶段中,移动设备决策其服务请求至云端处理的部分;第二阶段中,云端系统根据所有移动设备的服务请求到达率决策服务请求处理的资源分配。移动设备的目标是最小化功耗和服务请求响应时间,而云端系统的目标是最大化收益。基于向后归纳原则,利用凸优化方法求解了嵌套式两阶段博弈过程中移动设备和云端系统的最优策略,并证明算法可以产生唯一Nash均衡解。实验结果表明,比较基准算法,嵌套式两阶段博弈算法可以使移动设备同步降低平均功耗和平均服务请求响应时间分别约21. 8%和31. 9%。     

基于包簇映射的云计算资源分配策略

提出了一种基于包簇映射的云计算资源分配策略。在包、簇概念下,资源可共享,任务调度更为灵活,资源利用率更高。将多目标遗传算法与改进的蚂蚁算法动态融合,提出了一种基于成本最优的云计算资源分配算法。该算法在任务前期利用遗传算法快速随机的全局搜索能力,产生初始信息素,在任务后期通过蚂蚁算法蚂蚁间的信息交流和正反馈机制,寻找资源分配的最优解。实验结果表明,在包、簇概念下,该混合式调度算法能够显著降低云计算系统的任务完成时间和任务执行平均成本,有效减少簇结点的使用数量,提高资源利用率。     

基于组合双向拍卖与信任的多云计算资源分配与定价研究*

随着云计算市场规模的急剧增长,云计算资源的分配和定价成为了云计算市场的一个重要问题.针对当前云计算资源分配中将定价和信任相结合研究的不足,研究基于组合双向拍卖和信任的多云计算资源分配与定价算法,从价格和信任两方面来衡量云计算资源提供商的“综合竞争力”,激励综合竞争力高的云资源提供商获得更多的效用.实验仿真表明该算法满足激励兼容性和交易效用可激励云计算资源提供商提高综合竞争力.     

基于云计算的高校数字化资源整合系统方案

分析了高校数字化资源的现状及所面临的问题,介绍了云计算的结构模型,借助开源云计算系统Hadoop,给出了基于云计算的数字化资源整合系统方案.搭建了小型云计算集群,给出了配置方法,并对系统的输入输出性能进行了实验,验证了该方案在数字化资源整合研究中的可行性.     

云计算研究综述

介绍了云计算产生的背景和云计算的定义,辨析了云计算与其他计算形式的区别,阐述了云计算的特点及其体系结构,展望了云计算的发展前景。     

云计算的关键技术在高校图书馆中的应用

介绍了云计算的内涵及特征,分析了云计算环境下高校图书馆建设的现实需求,探讨了云计算的关键技术在高校图书馆的应用,指出云计算为高校图书馆建设和发展提供了新的技术支持。     

基于云计算的配电网脆弱性分析系统的设计

本文针对配电系统的脆弱性评估与控制问题,将云计算理论应用到配电网脆弱性的分析研究中,设计了基于云计算的配电网系统分层控制结构,并利用风险评估的风险指标实现了配电网脆弱性评估的功能.     

引入资源即服务的云计算架构及其应用

提出引入资源的四层云计算构架,阐述资源在云环境中的必要性.同时从资源的角度,给出云和云计算的概念.设计云计算环境下的数据采集模型,并从数据资源的角度,设计应用广义搜索树的面向云计算的数据预处理机制.与已有的云计算构架对比,该构架更能体现出云计算技术的特性,为云计算提供了一个思考方向.