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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...
Cloud computing environments mainly focus on the delivery of resources, platforms, and applications as services to users over the Internet. Cloud promises users access to as many resources as they need, making use of an elastic provisioning of resources. The cloud technology has gained popularity in recent years as the new paradigm in the IT industry. The number of users of Cloud services has been...
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...
The use of public clouds to extend the capacity of private resources has become a popular manner to achieve elasticity in the available in-house computational power to meet deadlines. Schedulers for such hybrid clouds have the role of deciding which types of instances should be leased in a pay-per-use basis to fulfill application demands. Often these schedulers assume a costless private cloud, which...
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