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In this paper, we propose a flexible workflow scheduler that facilitates the replacement of the objective function according to the user's needs. The possibility of replacing the objective function extends the usability of the scheduler for a variety of objectives. The proposed flexible scheduler uses Particle Swarm Optimization (PSO) to assist the production of schedules on cloud resources. We perform...
In this paper, we propose a procedure based on Particle Swarm Optimization (PSO) to guide the user in splitting an amount of CPU capacity (sum of frequencies) among a fixed number of resources in order to minimize the execution time (makespan) of the workflow. The proposed procedure was evaluated and compared with a naive approach, which selects only identical CPU frequency configurations for resources...
Cloud computing is a particularly interesting and truly complex concept of providing services over networks on demand. Many tools have previously been created to simulate the work of the clouds, such as CloudSim. The main use of these tools is evaluation and testing of architectures and services before deployment on network centers and hosts in order to avoid any potential failures or inconveniences...
In this paper, we address the two-stage assembly scheduling problem to minimize maximum lateness where setup times are treated as separate and sequence-independent. This problem has many applications including computer assembly problem. We propose a dominance relation and present three heuristics. Computational experiments are conducted to compare the proposed heuristics which show that particle swarm...
The assembly flowshop scheduling problem has been addressed recently in the literature. There are many problems that can be modeled as assembly flowshop scheduling problems including queries scheduling on distributed database systems and computer manufacturing. The problem has been addressed with respect to either makespan or total completion time criterion in the literature. In this paper, we address...
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