| Reference : Metaheuristics for the Virtual Machine Mapping Problem in Clouds |
| Scientific journals : Article | |||
| Engineering, computing & technology : Computer science | |||
| Security, Reliability and Trust | |||
| http://hdl.handle.net/10993/30192 | |||
| Metaheuristics for the Virtual Machine Mapping Problem in Clouds | |
| English | |
Nesmachnow, Sergio  [> >] | |
| Dorronsoro, Bernabé [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >] | |
| Talbi, El-Ghazali [> >] | |
| Bouvry, Pascal [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >] | |
| Oct-2015 | |
| Informatica | |
| 26 | |
| 1 | |
| 111-134 | |
| Yes | |
| International | |
| [en] cloud computing ; planning ; brokering | |
| [en] 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 prebooked resources from a cloud broker, maximizing the broker profit. Three metaheuristic are studied: Simulated Annealing, Genetic Algorithm, and hybrid Evolutionary Algorithm. The experimental 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. | |
| University of Luxembourg: High Performance Computing - ULHPC | |
| http://hdl.handle.net/10993/30192 | |
| http://www.mii.lt/informatica/pdf/INFO1043.pdf | |
| FnR ; FNR6466384 > Pascal Bouvry > IShOP > Internet Shopping Optimization Project > 01/03/2014 > 28/02/2017 > 2013 |
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