基于pareto的遗传算法在云代理环境下优化VM请求分配

Y. Kessaci, N. Melab, E. Talbi
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引用次数: 44

摘要

在本文中,我们讨论了云代理在三层云基础架构中的VM请求分配优化问题。我们研究了基于pareto的元启发式方法,以考虑多个以客户端和代理为中心的优化标准。提出了一种可以集成到云代理中的多目标遗传算法(MOGA-CB)。在优化过程中要考虑两个目标:最小化所选VM实例的响应时间和成本,以满足客户,并最大化代理的利润。该方法已经使用不同类型的Amazon EC2实例及其定价历史的实际数据进行了实验。已报道的结果表明,MOGA-CB提供了有效的Pareto解集。
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A pareto-based genetic algorithm for optimized assignment of VM requests on a cloud brokering environment
In this paper, we deal with cloud brokering for the assignment optimization of VM requests in three-tier cloud infrastructures. We investigate the Pareto-based meta-heuristic approach to take into account multiple client and broker-centric optimization criteria. We propose a new multi-objective Genetic Algorithm (MOGA-CB ) that can be integrated in a cloud broker. Two objectives are considered in the optimization process: minimizing both the response time and the cost of the selected VM instances to satisfy the clients and to maximize the profit of the broker. The approach has been experimented using realistic data of different types of Amazon EC2 instances and their pricing history. The reported results show that MOGA-CB provides efficiently effective Pareto sets of solutions.
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