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Load balancing is a major problem in grid computing systems to balance the computing resources are used to achieve optimal load processing time . The method used in load balancing by adjusting burden on computing resources that will be provided . Coordination of each computing resource is done by looking at the ability of each computing resource . Load balancing algorithm for heterogeneous computing...
Genetic Annealing Algorithm (GAA) combines with simulated annealing algorithm and genetic algorithms, which is one of the most representative algorithms to be applied into the protein structure prediction (PSP), but it requires computing power for the complexity of the algorithm itself. So a parallel GAA was proposed, which was run on the grid system. In this paper, we established a three-node grid...
Medicine-product-quality-estimation (MPQE) is a key stage of medicine services and manages. Especially, the Chinese medicine products consist complicated compositions from a variety of different natural arias and provided by different local manufactories. In the total MPQE process, an full computer-execution-process of MPQE including two intelligent algorithms, namely a specially composed Genetic-algorithm...
Grid computing is an innovative approach permitting the use of computing resources which are far apart and connected by Wide Area Networks. This recent technology has become extremely popular to optimize computing resources and manage data and computing workloads. The aim of this paper is to propose a metacomputing approach for the winner determination problem in combinatorial auctions (WDP). The...
Support vector machine is a machine learning method which is based on structural risk minimization principle. The traditional parameter optimization methods of support vector regression mainly employ grid search method and so on. These methods have shortcomings of being guided by human experience and time-consuming. In recent years, many intelligent search algorithms are used for SVR parameter optimization...
In the data grid environment, when users access to files, how to select the best site to obtain files from multiple replicas and reach the highest QOS (quality of service) in the cost of same price is a problem that need to be studied urgently, that is replica selection. In this paper, it proposes a new combination algorithm based on genetic algorithm and ant algorithm, which not only solves the inefficient...
The injection mold optimization problems always require huge computer resources, so the grid is a good choice for solving these problems. But for the heterogeneous, distributed and dynamic characters of the grid resources, it is difficult to finish the complex problems efficiently in collaborative way by grid. Based on the Globus Toolkits 4, a four-layer Mold Design Grid (MDG) platform was constructed...
This paper presents how it is possible to increase the genetic programming (GP) computing power (CP) for free, via volunteer computing (VC), using the well known framework BOINC plus a new ``virtualization'' layer which adds all the benefits from the virtualization paradigm. Two different experiments, employing a standard GP tool and a complex GP system, are performed -with distributed PCs over several...
In order to make full use of resources in distributed parallel computing system, and reduce general time cost for performing the algorithm, task scheduling and resource management model and low-layer resource supervision-control model are designed and implemented. The unpredictable system behavior is resolved, which is caused by dynamic change resources. The dynamic join-in of resources is allowed...
This paper presents a formulation of outage planning for electric power facilities treated as a combinatorial optimization problem considering power supply reliability. We utilize two indices to evaluate a security level of system configurations during outage works. The indices are defined as power supply shortage assuming N-2 contingencies and transmission loss assuming N-1 contingencies. A lot of...
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