面向成本优化的SBS虚拟化资源分配

在部署云应用问题中,对于结构复杂的基于SBS的资源优化分配问题,目前尚缺少深入研究.针对这一问题,提出了组件服务资源配置的概念及其确定方法,基于此将SBS的资源优化分配建模为资源配置的组合优化.为求解优化模型,给出了一种改进了交叉算子和变异算子的遗传算法.实验验证了优化模型的有效性,同时表明提出的遗传算法具有较快的收敛速度,且与线性规划相比,虽然最优解的质量相近,但是在较大规模问题上求解效率明显优于后者.

Cost Oriented Virtualized Resource Optimization Allocation for SBS

When deploying applications in cloud environments， there are few researches on the optimal resource allocation for cloud applications described as service based software systems (SBS). To solve the problem， resource configuration (RC) was defined， and a method for identifying all the RCs of any component services was proposed. Based on this， the resource allocation for SBS was modeled as combination optimization of RCs， and a genetic algorithm (GA) with improved cross operator and mutation operator was presented to solve the optimization model. Effectiveness of the model was proved by the experiment results， and it was showed that the proposed GA converged fast. In addition， similar optimal solutions could be obtained by the GA with linear programing， and it was more efficiency to deal with larger problem.