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General queueing modeling method, Stochastic Timed Automation, is employed to model the Semiconductor Wafer Fabrication System because of its flexibility and fidelity. The machine allocation is formulated as a stochastic integer programming problem with the objective to optimize the throughput of the Semiconductor Wafer Fabrication System. And we propose an Optimal Computing Budget Allocation-based...
The processing framework of large-scale data is becoming a major concern due to an explosive growth of data intensive applications in the cloud environment, such as MapReduce/Hadoop architecture. Many virtual machines (VMs) are used for processing large-scale data of cloud applications. Therefore, the total completion time of a task is an important index to evaluate the cloud performance. The access...
As a new computing paradigm, cloud computing has significantly contributed to the rapid development of massive data centers. However, the corresponding energy issue becomes increasingly challenging. In this paper, we focus on the energy saving issue for virtual machine (VM) selections on an overloaded host in a cloud computing environment. We analyze the energy influencing factors during a VM migration,...
With the development of cloud computing, there is an increasing number of market-based mechanisms for cloud resource allocation. Inspired by the emerging group-buying websites, we advocate that group-buying can be applied to cloud resource allocation, and thus cloud providers can benefit from demand aggregation due to the advantage of group-buying in attracting customers, while cloud users can enjoy...
Deformable models have been quite popular in medical image analysis, particularly in image segmentation. However, when applied to 3D volumetric data, their high computational cost can be a problem. In this paper, we describe a new efficient 3D segmentation method based on deformable simplex meshes. The greedy algorithm, which has proven more computational efficient and robust than physics-based method,...
Influence maximization is to find a small set of most influential nodes in the social networks to maximize their aggregated influence in the network. The high complexity of the classical greedy algorithm cannot be well suited for the moderate or large scale networks. It is necessary to develop a more efficient algorithm, not sensitive to the scale of the social network. In this paper, we propose an...
In the present work radial basis function (RBF) method, combined with improved data reduction algorithm, is presented as a unified methodology for efficient computational static aeroelastic simulations and volume mesh deformation. This method has been implemented as an extension of in-house hybrid unstructured Reynolds-Averaged Navier-Stokes solver coupled with an open source finite element solver...
Taking advantage of the structures inherent in many sparse decompositions constitutes a promising research axis. In this paper, we address this problem from a Bayesian point of view. We exploit a Boltzmann machine, allowing to take a large variety of structures into account, and focus on the resolution of a joint maximum a posteriori problem. The proposed algorithm, called Structured Bayesian Orthogonal...
We propose a novel deadline-based strategy in scheduling and rescheduling workflow applications on a heterogeneous Grid system. Instead of minimizing the makespan of a job by a greedy algorithm, our approach schedules tasks so that the overall job meets its deadline. The key innovation is how we allow some tasks to be rescheduled, in light of later job requests, to a different time slot or another...
Through traditional Snake model, contour points could not be converged accurately towards object boundary of deeply concave region and complex region. Aiming at this shortcoming, this paper improved internal energy from two aspects: convergent force from contour points to their center and area surrounded by contour points. And the paper used greedy algorithm of alternation of improved Snake model...
Data Stream mining (DSM) is claimed to be the successor of traditional data mining where it is capable of mining continuous incoming data streams in real-time with an acceptable performance. Nowadays many computer applications evolved to online and on-demand basis, fresh data are feeding in at high speeds. Not only a decision response needs to be made rapidly, the trained decision tree models would...
We study the online stochastic bipartite matching problem, in a form motivated by display ad allocation on the Internet. In the online, but adversarial case, the celebrated result of Karp, Vazirani and Vazirani gives an approximation ratio of 1- 1/e ?? 0.632, a very familiar bound that holds for many online problems; further, the bound is tight in this case. In the online, stochastic case when nodes...
Traditional security model, where the identity of all possible requesting subjects must be pre-registered in advance, is not suitable for the distributed applications with strong real-time requirements. A promising approach is represented by automated trust negotiation, which establishes trust between strangers through the exchange of digital credentials and the use of access control policies. As...
The advent of microarray technologies has made the experimental study of gene expression faster and more efficient. It is an important task to analyze the gene expression data acquired from the microarray experiments. Biclustering is a popular method to search a subset of genes which exhibit similar expression patterns along a subset of conditions in the gene expression matrix. In this paper, we propose...
We present a technique for transforming classical approximation algorithms into constant-time algorithms that approximate the size of the optimal solution. Our technique is applicable to a certain subclass of algorithms that compute a solution in a constant number of phases. The technique is based on greedily considering local improvements in random order.The problems amenable to our technique include...
The NTRU algorithm is a public key system based on ring, its appearance opened up a new field of application and research for the public key system. In this paper, we present a new method to enhance the executive speed of NTRU algorithm. First, we analyze the polynomial coefficients to find out the distribution characteristics of patterns,such as "11", "101" and so on, which are...
In this paper we study the call admission control problem to optimize the network operators' revenue guaranteeing the quality of service to the end users. We consider a network scenario where each class of service is characterized by a different constant bit rate and an associated revenue. We formulate the problem as a Semi-Markov Decision Process, and we use a model based Reinforcement Learning approach...
This paper introduces the innovative Grid-based RTSOA frameworks, and specializes these frameworks to the exciting context of Data Transformation services over Grids, which play a significant role in the context of data-intensive e-science Grid applications. Also, in order to efficiently support Grid-based RTSOA frameworks, we provide a complete model based on the data compression/approximation paradigm,...
Dynamic power dissipation on I/O buses is an important issue for high-speed communication between chips. One can use coding techniques to reduce the number of transitions, which will reduce the dynamic power. Bus-invert coding is one popular technique for interchip buses, where the dominant contribution is from the self-capacitance of the wires. This algorithm uses an invert line to signal whether...
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