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Huang Y.,Fuzhou University | Huang Y.,Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing | Lan X.,Fuzhou University | Lan X.,Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing | And 2 more authors.
Proceedings - 2015 12th Web Information System and Application Conference, WISA 2015 | Year: 2015

Hadoop is an open source software framework of distributed processing of big data. There are many kinds of services in Hadoop ecosystem, such as HDFS, Map-Reduce, HBase, Hive, Yarn, Flume, Spark, Storm, Zookeeper, and so on, which increase the complexity of deployment and configuration. It takes plenty of time to construct a Hadoop cluster. Although there are some management tools which help administrators deploy and configure Hadoop clusters automatically, they usually provide a fixed solution. So administrators couldn't construct their Hadoop clusters according to different management requirements by the tools. Software architecture acts as a bridge between requirements and implementations. It has been used to reduce the complexity and cost mainly resulted from the difficulties faced by understanding the large-scale and complex software system. This paper proposes a model based approach to Hadoop deployment and configuration which help administrators construct Hadoop clusters in a simple but powerful enough manner. First, we provide the unified models of Hadoop software architecture, according to the domain knowledge of current Hadoop deployment and configuration. Second, we provide a framework with a set of definable rules for domain experts to describe their solutions to deploy and configure Hadoop clusters. Thus, administrators can use various custom solutions to automatically deploy and configure their Hadoop clusters according to different management requirements. In addition, a real-world experiment demonstrates the feasibility, effectiveness and benefits of the new approach to Hadoop deployment and configuration. © 2015 IEEE. Source


Chen K.,Fuzhou University | Chen K.,Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing | Lin C.,Fuzhou University | Zhong S.,Fuzhou University | And 2 more authors.
Computer Science and Information Systems | Year: 2015

The Spatial Rich Model (SRM) generates powerful steganalysis features, but has high computational complexity since it requires calculating tens of thousands of convolutions with image noise residuals. Practical applications dealing with a massive amount of image transferred through the Internet would suffer a long computing time if using CPU. To accelerate the steganalysis, we present a parallel SRM feature extraction algorithm based on GPU architecture. We exploit parallelism of the algorithm, modify the original SRM extraction algorithm and employ some strategies to avoid the disadvantage of its sequentiality. Some OpenCL optimization technologies are also used to accelerate the extraction process, such as convolution unrolling, combined memory access, split-merge strategy for co-occurrence matrix calculation. The experimental results show that the speed of the proposed parallel extraction algorithm for different size images is 25~55 times faster than the original single thread algorithm. In addition, when using AMD GPU HD 6850, our algorithm runs 2~4.2 times faster than using a Intel Quad-core CPU. This indicates our algorithm makes good use of the GPU cores. © 2015 ComSIS Consortium. All rights reserved. Source


Chen X.,Fuzhou University | Chen X.,Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing | Li A.,Fuzhou University | Li A.,Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing | And 6 more authors.
Frontiers of Computer Science | Year: 2015

The internet of things (IoT) attracts great interest in many application domains concerned with monitoring and control of physical phenomena. However, application development is still one of the main hurdles to a wide adoption of IoT technology. Application development is done at a low level, very close to the operating system and requires programmers to focus on low-level system issues. The underlying APIs can be very complicated and the amount of data collected can be huge. This can be very hard to deal with as a developer. In this paper, we present a runtime model based approach to IoT application development. First, the manageability of sensor devices is abstracted as runtime models that are automatically connected with the corresponding systems. Second, a customized model is constructed according to a personalized application scenario and the synchronization between the customized model and sensor device runtime models is ensured through model transformation. Thus, all the application logic can be carried out by executing programs on the customized model. An experiment on a real-world application scenario demonstrates the feasibility, effectiveness, and benefits of the new approach to IoT application development. © 2015, Higher Education Press and Springer-Verlag Berlin Heidelberg. Source


Li A.,Fuzhou University | Chen X.,Fuzhou University | Xu Y.,State Grid Corporation of China | Zeng X.,Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing | And 2 more authors.
Proceedings - 2015 12th Web Information System and Application Conference, WISA 2015 | Year: 2015

In recent years, with the rapid development of Internet, those Query-Intensive web information systems can not meet the requirement of high performance, which mainly comes from the following two aspects. First, most database systems that web information systems use store the related data in disks, which causes the slow data access. Second, it is hard to support large numbers of users accessing in parallel due to the limitation of single server's physical resources, which causes the server overload. For solving the problems, this paper proposes a MMDB (Main-Memory Database) cluster based cloud platform for Query-Intensive web information systems. First, we design a MMDB cluster based web information system according to the current technology. Second, we develop a model-based cloud platform, which provides support for the MMDB cluster based web information system at an architecture level. The experiment on a real-world cloud demonstrates the feasibility, effectiveness and benefits of the new approach to improving the performance of those Query-Intensive web information systems. © 2015 IEEE. Source


Zeng X.,Fuzhou University | Zeng X.,Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing | Lan X.,Fuzhou University | Lan X.,Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing | And 3 more authors.
Proceedings - International Computer Software and Applications Conference | Year: 2015

Cloud management becomes increasingly complex and brings high costs, especially with the advent of hybrid cloud. In a hybrid cloud, numerous resources like Virtual Machines (VMs) and Physical Machines in different clouds have to be managed together to make the whole hybrid cloud work cost-effectively. For controlling the management cost, in particular the manual management cost, many programs have been developed to take over manual management tasks or reduce their complexity and difficulty. These programs are usually hard-coded by languages like Java and C++, which bring enough capability and flexibility but also cause high programming effort and cost. As the architecture-based runtime model is causally connected with the corresponding running system automatically, constructing a hybrid cloud management system based on the architecture-based runtime models of clouds can benefit from the model-specific natures, and thus reduce the development workload. This paper proposes a runtime architecture based approach to developing the management programs in a simple but powerful enough manner. First of all, the manageability (such as APIs, configuration files and scripts) of different kinds of clouds, is abstracted as a runtime architecture based model of cloud software architecture, which can automatically and immediately propagate any observable runtime changes of the target platforms to the corresponding architecture models, and vice versa. Second, we provide a unified model of cloud software architecture, according to the domain knowledge of current cloud platforms, such as Cloud Stack, Open Stack and Eucalyptus. Third, the synchronization between the unified model and cloud runtime models is ensured through model transformation, thus, all the management tasks of the hybrid cloud, could be carried out through executing programs on the unified model, which decreases the complexity of use and management. The experiment on a real-world hybrid cloud demonstrates the feasibility, effectiveness and benefits of the new approach to managing hybrid clouds. © 2015 IEEE. Source

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