Web services are widely used in modern software, providing diverse data and functionalities. Some data and functionalities are critical to an application’s execution and user experience, posing strict requirements on the Quality of Service (QoS) of their delivery (e.g., latency and reliability), which services often fail to meet. Previous studies show that composing homogeneous services, i.e., simultaneously invoking multiple services providing the same functionalities and returning the first response, can improve latency and reliability. However, this approach increases the workloads on cloud servers and causes additional network traffic, limiting its deployment at scale. Noting that services provide varying QoS across different locations, we introduce an approach that dynamically composes homogeneous services for each client, achieving the desired QoS for critical services while minimizing invocation costs. Specifically, our method probes the QoS of all homogeneous services for a client, then calculates an optimal composition strategy that meets QoS requirements at the lowest cost. The evaluation results show that our approach significantly improves the QoS invoking a single service (enhancing reliability to 100%, reducing average latency by 7% and tail latency by 35%) while incurring 50% less cost than static homogeneous composition, making it a useful tool for service-oriented applications.