在云环境下,用户能够方便地按需获取满足其要求的服务资源,而高质量的服务将受到用户的青睐.然而,云环境下的服务请求具有即时、并发以及大规模等特点,多个用户可能同时调用同一个高质量的服务,极有可能出现用户访问量超过服务的负载容量的情况,致使服务负载失衡,从而导致无法即时响应用户请求,服务提供能力急剧下降.针对这一问题,本文提出了面向云环境的一种负载感知的服务选择方法.该方法,首先构建了一个描述用户请求和服务QoS之间关系的用户满意度模型.其次,由服务的负载能力和用户的满意度获得服务的综合得分,并根据服务的综合得分对服务进行排名与选择.最后,在数据集上进行了大规模的实验,实验结果表明:负载感知的服务选择方法能在保证负载平衡的情况下有效地帮助用户选择满足需求的高质量的服务. In the cloud environment, users can easily access service resources that meet their requirements on demand, and high-quality services will be favored by users.However, service requests in cloud environments are characterized by instant, concurrent and large-scale, multiple Users may call the same high-quality service at the same time, and it is very likely that the user’s traffic will exceed the service’s load capacity, resulting in unbalanced service load, resulting in the inability to immediately respond to user requests and the sharp decline of service provision capabilities.In response to this problem, This paper proposes a load-aware service selection method for cloud environment.This method first builds a user satisfaction model that describes the relationship between user requests and service QoS.Secondly, from the service load capacity and user satisfaction Get the comprehensive score of the service, and rank and select the service according to the comprehensive scores of the service.Finally, a large-scale experiment is carried out on the data set, and the experimental results show that the load-sensing service selection method can guarantee the load balance Effectively help users choose to meet the needs of high-quality services.