This paper presents a strategy to allocate services on a Cloud system without overloading nodes and maintaining the system stability with minimum cost. We specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. A prototype meta-heuristic load balancer is demonstrated and experimental results are presented and discussed. We also propose a novel genetic algorithm, where population is seeded with the outputs of other meta-heuristic algorithms.

翻译：本文提出一种在云系统中分配服务的策略，旨在避免节点过载并以最低成本维持系统稳定性。我们构建了一个云资源利用的抽象模型，涵盖多种资源类型并考虑了服务迁移成本。文中展示了一个原型元启发式负载均衡器，呈现并讨论了实验结果。此外，我们提出了一种新颖的遗传算法，其初始种群由其他元启发式算法的输出结果进行初始化。