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This paper deals with the process of identifying the parameters of the dynamic equivalent (DE) load model of an active distribution system (ADN) simulated in RTDS using mean-variance mapping optimization (MVMO) algorithm. MVMO is an emerging variant of population-based, evolutionary optimization algorithm whose features include evolution of its solutions through a unique search mechanism within a...
Managing a one-way vehicle sharing system means periodically moving free access vehicles from excess to deficit stations in order to avoid local shortages. We perform a lower bound analysis for the static version of the resulting operational decision problem, and derive from this analysis two heuristic algorithms whose main feature is to be vehicle oriented, which means that they focus on the way...
Reproducibility of the execution of scientific applications on parallel and distributed systems is a growing interest, underlying the trustworthiness of the experiments and the conclusions derived from experiments. Dynamic loop scheduling (DLS) techniques are an effective approach towards performance improvement of scientific applications via load balancing. These techniques address algorithmic and...
Reproducibility of the execution of scientific applications on parallel and distributed systems is a growing concern, underlying the trustworthiness of the experiments and the conclusions derived from experiments. Dynamic loop scheduling (DLS) techniques are an effective approach towards performance improvement of scientific applications via load balancing. These techniques address algorithmic and...
In the intensive computation domain, the applications with high volume of data need strong processing power and considerable storage resources. To reach the required computation power, multiple machines should be associated in order to handle the distributed tasks. However, the heterogeneity of the associated machines is to be considered during the tasks scheduling. In this paper, we propose a new...
Scalability and reliability are among the main concerns in large-scale Software Defined Networking (SDN) application scenarios. A common approach is to use multiple distributed controllers, each managing one static partition of the network. In this paper, we show that dynamic mapping can improve efficiency in managing traffic load variations. We then propose BalCon (Balanced Controller): an algorithmic...
We have enabled work migration in the CoMD proxy application to study dynamic load imbalance. Proxy applications are developed to simplify studying parallel performance of scientific simulations and to test potential solutions for performance problems. However, proxy applications are typically too simple to allow work migration or to represent the load imbalance of their parent applications. To study...
Grid computing is the group of computer resources from numerous sites to achieve a common aspiration. The grid can be consideration of as a distributed system with non-interactive workloads that engross a great amount of files. In Grid computing, fault tolerance is a major predicament and of the metric which believe being most imperative since the resource failure affects job finishing, throughput,...
In this article, an efficient parallel algorithm for a hybrid CPU-GPU platform is proposed to enable large-scale molecular dynamics (MD) simulations of the metal solidification process. The results, implemented the parallel algorithm program on the hybrid CPU-GPU platform shows better performance than the program based on previous algorithms running on the CPU cluster platform. By contrast, the total...
In the HLA simulation system, there exist two kinds of model combination technology: the federation member level and the model level. In this paper, two kinds of model combination technology are introduced in detail, and through the comparison their advantages and disadvantages are analyzed. It shows that the combination on the member level is more applicable for the small simulation system, and the...
. In this paper, we proposed a new Energy Aware Load-Balancing Architecture (E-Balance) which balances the load across the network and it decreases energy consumption. Foremost of all, we proposed an optimal system model. And so, we figured out our system model by optimization solver. The optimal model had two grave problems: computation complexity and the demand for a global vision of network status...
In this paper, we present two distributed algorithms to compute an equilibrium, that is optimal with respect to strictly convex and separable cost functions, for controlled traffic flow dynamics over networks under constant exogenous inflows. The dynamics is modeled in continuous time by the Cell Transmission Model and a non-FIFO Dynamic Network Loading Model, with traffic control. The two algorithms...
In data centers, many tasks (services, virtual machines or computational jobs) share a single physical machine. We propose a new resource management model for such colocation. Our model uses two parameters of a task -- its size and its type -- to characterize how a task influences the performance of the other tasks allocated on the same machine. As typically a data~center hosts many similar, recurring...
Independent Joint Learning (IJL) was recently introduced as a learning-based approach to account for inverse dynamics (ID) model errors. The fundamental idea is to combine an ID model with learned torque error estimators that only rely on joint-local information. This approach improves task-to-task generalization and reduces learning times as each torque error estimators depends only on the state...
The use of GPU clusters for scientific applications in areas such as physics, chemistry and bioinformatics is becoming more widespread. These clusters frequently have different types of processing devices, such as CPUs and GPUs, which can themselves be heterogeneous. To use these devices in an efficient manner, it is crucial to find the right amount of work for each processor that balances the computational...
This work proposes a new path-planning framework that provides uniform coverage of 3D structures by employing an iterative strategy to improve the inspection path that benefits from remeshing-techniques, while the first full solution is computed very fast. The resulting paths inspect each detail of the structure from a distance that directly depends to the local geometrical complexity of the structure...
Rapid growth of internet and other technologies seems more challenging to develop the high speed networks with powerful capabilities in lower computational cost. To cover the above problem grid computing has emerged rapidly. The previous technologies such as distributed computing cluster computing, parallel computing, etc., facing the problem of space utilization. Using Grid Computing technologies...
Discrete event simulations (DES) are used in situations where we need to understand or describe complex phenomena. This paper describes an algorithm for dynamic orchestration of stochastic DES. To cope with long execution times in stochastic DES settings, we use MapReduce to achieve concurrent processing of the simulation on a distributed collection of machines. The proposed algorithm proactively...
Cloud Computing offers on demand provisioning of computing resources to users. Cloud service providers manage a large number of user requests to provide services according to user demands. Allocating and managing user requests to physical hardware is a challenging issue, because there is a need to create a load balance among available system resources. Effective load balancing saves operational costs,...
Load balancing is the key to many parallel and distributed applications. We consider the following load balancing problem: given any undirected connected graph and an initial weight distribution on the nodes, determine a schedule to move weights across edges so as to have (almost) equal weights on the nodes. Weights are moved across edges in rounds, and, in a round, weights are moved between the adjacent...
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