In order to reduce operation and maintenance expense and also increase the resource utilization rate,server consolidation and virtualization solutions have been adopted in modern cloud computing data ***,the schedulin...
In order to reduce operation and maintenance expense and also increase the resource utilization rate,server consolidation and virtualization solutions have been adopted in modern cloud computing data ***,the scheduling policies of virtual machine(VM) migration have been regarded as an effective method for energy *** this paper,we address the problem of VM consolidation in cloud data centers.A power aware scheduling algorithm THRUG,which is combined with a utilization threshold strategy and a VM selection policy,is *** tries to select the most appropriate VMs for migration each time when a physical machine(PM) is considered as being overloaded,such that the utilization of this PM is just not more than the utilization threshold,such that both the energy consumption and the number of VM migration can be *** experimental results show that compared with other algorithm,the proposed algorithm can effectively reduce the number of VM migrations as well as the energy consumption.
Application of cloud computing technologies in power system has made a great contribution to the establishment of smart grid. Among applications of smart grid, electrical load prediction plays an important role in eff...
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ISBN:
(纸本)9781509054442
Application of cloud computing technologies in power system has made a great contribution to the establishment of smart grid. Among applications of smart grid, electrical load prediction plays an important role in efficient use of power resource. However, the exponential growth of data has posed a great challenge to the existing algorithms. In this paper, we firstly propose a novel parallel hybrid algorithm, combining the Improved Particle Swarm Optimization (PSO) with ELM, named PIPSO-ELM. Here a modified particle swarm optimization is presented to find the optimal number of hidden neurons as well as the corresponding input weights and hidden biases. Furthermore, in the iterative search process of PSO, an update strategy employs the mutation operator of evolutionary algorithms is introduced for further improving the global search capability and convergence speed of PSO. After that, to handle the large-scale dataset efficiently, the parallel implementation of PIPSO-ELM is achieved using Spark. Finally, extensive experiments on real-life electrical load data and comprehensive evaluation are conducted to verify the performance of PIPSO-ELM in electrical load prediction. Extensive experimental results demonstrate that PIPSO-ELM outperforms the compared algorithms in terms of stability, efficiency and scalability simultaneously.
Effective user interest prediction is significant for service providers in a set of application scenarios such as user behavior analysis and resource recommendation. However, existing approaches are either incomplete ...
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Due to the diversification of software and hardware resources in cloud and ever-changing demand for deployment, Hadoop deployment is faced with great challenges in difficulty and complexity. Most of present researches...
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Due to the diversification of software and hardware resources in cloud and ever-changing demand for deployment, Hadoop deployment is faced with great challenges in difficulty and complexity. Most of present researches lie in environment configuration and parameter setting of deployment, they do not take into account diversification of infrastructure and scalability issues in cloud. In order to quickly customize, deploy and expand Hadoop services according to the demand, a model-driven approach to Hadoop deployment is proposed in the paper. Firstly, Hadoop demand and deployment models are presented. Secondly, the transformation method from the demand model to the deployment model is proposed. Thirdly, the bidirectional synchronization between Hadoop deployment model and running system is realized based on runtime model.
The tremendous parallel computing ability of cloud computing encourages investigators to research its drawbacks and advantages on processing large-scale scientific applications such as workflows. The current cloud mar...
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Through MATLAB, the paper makes a comparison between Principal Component Analysis (PCA)face recognition algorithm and Adaboost recognition algorithm and selects the algorithm with higher recognition rates to develop a...
Through MATLAB, the paper makes a comparison between Principal Component Analysis (PCA)face recognition algorithm and Adaboost recognition algorithm and selects the algorithm with higher recognition rates to develop an auto face recognition system. The paper explicates primary techniques the system adopts and its specific realization process. By downloading face database online, the paper conducts an all-round test to the system, the result of which proves that this face recognition system is completely practical and feasible.
Objective: to explore and interpret the model of diabetes mobile online management from the perspective of web model. Methods: from the interdisciplinary perspective, combined with economics, management science and co...
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Objective: to explore and interpret the model of diabetes mobile online management from the perspective of web model. Methods: from the interdisciplinary perspective, combined with economics, management science and computer science, with the only dynamic model in microeconomics—the cobweb model, from chronic disease management, Internet + medical application, analyze the application of Internet technology in diabetes management. Results: through mobile Internet technology, optimized the unit of diabetes management and realized the "monitoring - assessment - intervention" closed-loop management. Conclusion: explore the digital medical health industry in periodic production commodity price fluctuations and other activities, can establish early warning system and mechanism, to improve patients and their families to the cognitive level of diabetes, according to the medical behavior and self management ability.
In the existing cloud computing environment, batch scheduling strategies mainly focus on the management of resources allocation. This paper provides the task scheduling algorithm based on service quality which fully c...
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To achieve objective image correction quality assessment results that are consistent with subjective perception, we create an Image Color Correction Database (ICCD). ICCD contains a variety of types and scales of colo...
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Signature verification is an important part of digital forensics. In order to solve the shortcomings of manual identification in technical accuracy and subjectivity, this paper proposed an off-line signature identific...
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Signature verification is an important part of digital forensics. In order to solve the shortcomings of manual identification in technical accuracy and subjectivity, this paper proposed an off-line signature identification method based on Support Vector Machine (SVM). A powerful feature set is collected by extracting grid features and global features of a signature picture. The method is applied for identifying different writing systems and the highest correct probability of identification arrives at 100%. The results indicated that the method is workable and can be an effectively technical support for digital forensics.
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