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We analyze the performance of the randomized multiple- choice allocation process in the fixed density model. We show that the allocation process leads to O(log log n) expected maximal bin load when Theta(n) balls are allocated into n bins, where each ball is inserted into the less loaded bin among two bins chosen independently and according to two fixed but possibly different bounded probability densities...
Stochastic simulations may require many replications until their results are statistically significant. Each replication corresponds to a standalone simulation job, so that these can be computed in parallel. This paper presents a grid-inspired approach to distribute such independent jobs over a set of computing resources that host simulation services, all of which are managed by a central master service...
Aiming at intensive data processing in grid environment, a grid platform IDPGP is constructed based on Globus Toolkit 4, OGSA-DAI, Condor and PBS. This platform mainly provides grid information acquirement service, grid resource management service, data access and integration service, which can realize grid resources sharing, intensive data access and processing. In the grid resource management service,...
In this paper, we describe a cluster server, Linux virtual server cluster, formed by various inexpensive personal computers for scientific computing. This cluster has many favorable features, including lower cost, load balancing, and dynamic scalability. Application of this cluster in the simulation of photochemistry reaction is also presented.
Data allocation comprises data placement or migration into or between the data servers in a distributed data sharing system. In the process of data placement, static equations would mostly select only the best data servers. This would overload some of the data servers. An algorithm for optimizing file-placement in data grid environment (DGE) is presented. The algorithm adapts game theory and fictitious...
In this paper, we address the service consolidation problem: given a data-center, a set of servers and a set of multi-tiered services or applications, the problem is to allocate services to the available servers in order to minimize the number of servers to use while avoiding the overloading of system resources and satisfying end-to-end response time constraints. Exploiting queueing networks theory,...
Multicore processors promise continued hardware performance improvements even as single-core performance flattens out. However they also enable increasingly complex application software that threatens to obfuscate application-level performance. This paper applies operational analysis to the problem of understanding and predicting application-level performance in parallel servers. We present operational...
Scientific simulation and modeling often aid in making critical decisions in such diverse fields as city planning, severe weather prediction and influenza modeling. In some of these situations the computations operate under strict deadlines, after which point the results may have very little value. In these cases of urgent computing, it is imperative that these computations begin execution as quickly...
A distributed application can be implemented as components, which might be available on a single host or distributed across various hosts. However, in a pervasive environment, such applications cannot be described statically in terms of the required components. This is because in such environments, the device participation is dynamic and the components described in application may not be available...
Performance analysis is one of the most important aspects in the research of workflow technology. In this paper, we put forward an approximate performance analysis method of workflow model with resource constraints, which combines queuing theory and stochastic Petri net. In the end, an example is given to illustrates our method can solve real-world problems efficiently
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