References of "El-Ghazali, Talbi"
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See detailA parallel hybrid evolutionary algorithm for the optimization of broker virtual machines subletting in cloud systems
iturriaga, Santiago; Nesmachnow, Sergio; Dorronsoro, Bernabe et al

in International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (2013)

This article presents a new parallel hybrid evolutionary algorithm to solve the problem of virtual machines subletting in cloud systems. The problem deals with the efficient allocation of a set of virtual ... [more ▼]

This article presents a new parallel hybrid evolutionary algorithm to solve the problem of virtual machines subletting in cloud systems. The problem deals with the efficient allocation of a set of virtual machine requests from customers into available pre-booked resources from a cloud broker, in order to maximize the broker profit. The proposed parallel algorithm uses a distributed subpopulations model, and a Simulated Annealing operator. The experimental evaluation analyzes the profit and makespan results of the proposed methods over a set of problem instances that account for realistic workloads and scenarios using real data from cloud providers. A comparison with greedy heuristics indicates that the proposed method is able to compute solutions with up to 133.8% improvement in the profit values, while accounting for accurate makespan results. [less ▲]

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See detailList scheduling heuristics for virtual machine mapping in cloud systems
nesmachnow, sergio; iturriaga, santiago; dorronsoro, bernabe et al

in VI Latin American Symposium on High Performance Computing (HPCLatam) (2013)

This article introduces the formulation of the VirtualMachine Planning Problem in cloud computing systems. It deals with the efficient allocation of a set of virtual machine requests from customers into ... [more ▼]

This article introduces the formulation of the VirtualMachine Planning Problem in cloud computing systems. It deals with the efficient allocation of a set of virtual machine requests from customers into the available pre-booked resources the broker has in a number of cloud providers, maximizing the broker profit. Eight list scheduling heuristics are proposed to solve the problem, by taking into account different criteria for mapping request to available virtual machines. The experimental evaluation analyzes the profit, makespan, and flowtime results of the proposed methods over a set of 400 problem instances that account for realistic workloads and scenarios using real data from cloud providers. [less ▲]

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