云计算环境下基于用户行为特征的资源分配策略

User-Aware Resource Provision Policy for Cloud Computing

资源分配策略是云计算研究领域中的一项重要研究点,研究人员提出了多种资源共享与分配策略,然而很少有工作关注不同云计算用户群体的行为习惯对资源分配策略的影响.提出的基于用户行为特征的资源分配策略就是通过统计用户工作习惯与任务完成时间期望值的变化规律,建立用户行为特征信息表,从而预测出不同时间片内用户的任务提交规律以及用户期望完成时间,动态调整云计算系统的资源分配策略,使得系统在满足用户预期任务完成时间的前提下实现任务并发最大化,提升单位资源的用户满意度.HUTAF(Huawei unitfied test automation framework)云测试平台是华为公司自行研发的云测试平台,并基于该平台开展各种策略下的资源利用率与用户满意度实验.实验结果表明,该策略提升了整个系统在满足用户期望完成时间的前提下的总任务并发数,有效降低了IaaS供应商的运营成本.

Cloud computing has become a hot topic, and researchers have proposed various resource sharing techniques and resource provision techniques. However, few literatures pay attentions to the influence of behavior habits of user for resource provision policy. This paper proposes a behavior based resource provision policy for cloud computing, and designs an algorithm BBTSA to analyze the user behavior data. Then, we can utilize probably theory to forecast the set of submitted task and expectation completing time of task at next time segment from the statistic results. After creating the policy table, system can dynamically adjust the resource provision policy according to the policy table and get the max VOC of unit resource. In order to evaluate the effect, we have done four-series experiments on HUTAF which is a cloud testing platform and developed by Huawei. The results indicate that the proposed resource provision policy is effective for improving the VOC and without increasing investment. The algorithm BBTSA is good for IaaS service companies to reduce investment.