Abstract
This article presents sequential and parallel metaheuristics to solve the virtual machines subletting problem in cloud systems, which deals with allocating virtual machine requests into pre- booked resources from a cloud broker, maximizing the broker profit. Three metaheuristic are stud- ied: Simulated Annealing, Genetic Algorithm, and hybrid Evolutionary Algorithm. The experimen- tal evaluation over instances accounting for workloads and scenarios using real data from cloud providers, indicates that the parallel hybrid Evolutionary Algorithm is the best method to solve the problem, computing solutions with up to 368.9% profit improvement over greedy heuristics results while accounting for accurate makespan and flowtime values.
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