云环境下基于SLA的优化资源分配研究

Research on SLA-based optimizing resource allocation in cloud

针对云计算环境下如何高效分配资源,实现资源供应者利润最大化这一难题,提出了一种基于服务级别协议(SLA)的动态云资源分配策略。该策略通过将SLA中的计算力、网络带宽、数据存储等属性作为优化参数,构造了一种服务请求与资源的映射模型,同时设计相应的效用函数,并结合改进的与模拟退火算法相融合的混合粒子群算法(SA-PSO),实现云环境下的优化资源分配。实验分析结果表明,基于SLA参数的SA-PSO算法具有更好的全局最优值,在给定虚拟资源相同情况下,调用该算法完成用户任务实现的利润更高。

For the problem, how to efficiently allocate the resource to ensure the service provider to make the maximize profit in cloud computing, this paper proposes a dynamic cloud resource allocation policy based on Service Level Agreement（SLA）, by considering the SLA properties, containing computing capacity, network bandwidth and data storage as optimization parameters. A kind of mapping model between service request and resource allocation is given, at the same time, the corresponding utility function is designed. An improved hybrid Particle Swarm Optimization algorithm based on Simulated Annealing（SA-PSO）is analyzed. Experimental results show that the SLA-based parameters SA-PSO has better global optimality. It can obtain higher benefits than other algorithm under the same condition.