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Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous distributed computing systems and it is also an appealing NP-complete problem. There is a number of heuristic and meta-heuristic algorithms that were tailored to deal with scheduling of independent jobs. In this paper we investigate the efficiency of differential evolution on the scheduling problem.
Scheduling is a key problem in distributed heterogeneous computing systems in order to benefit from the large computing capacity of such systems and is an NP-complete problem. In this paper, we present a Particle Swarm Optimization (PSO) approach for this problem. PSO is a population-based search algorithm based on the simulation of the social behavior of bird flocking and fish schooling. Particles...
Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous distributed computing systems and is an NP-complete problem. Therefore using meta-heuristic algorithms is a suitable approach in order to cope with its difficulty. In meta-heuristic algorithms, generating individuals in the initial step has an important effect on the convergence behavior of the algorithm and...
Job Scheduling on Computational Grids is gaining importance due to the need for efficient large-scale Grid-enabled applications. Among different optimization techniques addressed for the problem, Genetic Algorithm (GA) is a popular class of solution methods. As GAs are high level algorithms, specific algorithms can be designed by choosing the genetic operators as well as the evolutionary strategies...
Multiprocessors have emerged as a powerful computing means for running real-time applications, especially where a uniprocessor system would not be sufficient enough to execute all the tasks. The high performance and reliability of multiprocessors have made them a powerful computing resource. Such computing environment requires an efficient algorithm to determine when and on which processor a given...
The scheduling problem in distributed data-intensive computing environments has been an active research topic due to immense practical applications. In this paper, we model the scheduling problem for work-flow applications in distributed data-intensive computing environments (FDSP) and make an attempt to formulate and solve the problem using a particle swarm optimization approach. We illustrate the...
In order to be able to take full advantage of a distributed computing facility it is important not only to distribute the hardware but also to distribute the control of these resources. However, distributed control is very different from centralized control since at any time, several processes or several controllers may observe different and inconsistent views of the global system state. The task...
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