A Unified Framework of the Cloud Computing Service Model

After a comprehensive literature review and analysis, a unified cloud computing framework is proposed, which comprises MapReduce, a vertual machine, Hadoop distributed file system （HDFS）, Hbase, Hadoop, and virtualization. This study also compares Microsoft, Trend Micro, and the proposed unified cloud computing architecture to show that the proposed unified framework of the cloud computing service model is comprehensive and appropriate for the current complexities of businesses. The findings of this study can contribute to the knowledge for academics and practitioners to understand, assess, and analyze a cloud computing service application.

A Multi-Level Authorization Based Tenant Separation Mechanism in Cloud Computing Environment

Separation issue is one of the most important problems about cloud computing security. Tenants should be separated from each other based on cloud infrastructure and different users from one tenant should be separated from each other with the constraint of security policies. Learning from the notion of trusted cloud computing and trustworthiness in cloud, in this paper, a multi-level authorization separation model is formally described, and a series of rules are proposed to summarize the separation property of this model. The correctness of the rules is proved. Furthermore, based on this model, a tenant separation mechanism is deployed in a real world mixed-critical information system. Performance benchmarks have shown the availability and efficiency of this mechanism.

Parallelized User Clicks Recognition from Massive HTTP Data Based on Dependency Graph Model

With increasingly complex website structure and continuously advancing web technologies,accurate user clicks recognition from massive HTTP data,which is critical for web usage mining,becomes more difficult.In this paper,we propose a dependency graph model to describe the relationships between web requests.Based on this model,we design and implement a heuristic parallel algorithm to distinguish user clicks with the assistance of cloud computing technology.We evaluate the proposed algorithm with real massive data.The size of the dataset collected from a mobile core network is 228.7GB.It covers more than three million users.The experiment results demonstrate that the proposed algorithm can achieve higher accuracy than previous methods.

Research on anti-attack performance of a private cloud safety computer based on the Markov-Percopy dynamic heterogeneous redundancy structure

With the increasing computing demand of train operation control systems,the application of cloud computing technology on safety computer platforms of train control system has become a research hotspot in recent years.How to improve the safety and availability of private cloud safety computers is the key problem when applying cloud computing to train operation control systems.Because the cloud computing platform is in an open network environment,it can face many security loopholes and malicious network at-tacks.Therefore,it is necessary to change the existing safety computer platform structure to improve the attack resistance of the private cloud safety computer platform,thereby enhancing its safety and reliability.Firstly,a private cloud safety computer platform architecture based on dynamic heterogeneous redundant(DHR)structure is proposed,and a dynamic migration mechanism for heterogeneous executives is designed.Then,a generalized stochastic Petri net(GSPN)model of a private cloud safety computer platform based on DHR is established,and its steady-state probability is solved by using its isomorphism with the continuous-time Markov model(CTMC)to analyse the impact of different system structures and executive migration mechanisms on the system's anti-attack performance.Finally,through experimental verifcation,the system structure proposed in this paper can improve the anti-attack capability of the private cloud safety computer platform,thereby improving its safety and reliability.