In IaaS cloud services, QoS of network applications (NW-Apps) may degrade due to location factors such as significant distance between a server-side application (server) of a NW-App at a data center and a client-side application (client) of the NW-App at a client terminal. In order to shorten the distance and to improve the QoS, server migration services (SMSes) have been proposed. In SMSes, servers may migrate between different computers (called work places, WPs) on a network to prevent QoS degradation caused by the changes of client locations. Although server migrations can improve QoS of NW-Apps, they also generate a huge amount of traffic (server migration traffic) in the network. This paper focuses on a server location decision problem where the location of a server is decided in an on-line manner so that QoS of a NW-App is improved under the constraint that the server migration traffic has to be suppressed below an acceptable level. For the problem, we propose a practical on-line algorithm. The key idea behind the proposed algorithm is that the location of the server is decided with consideration of the QoS degradation in the future. The algorithm defines the averagely good location for the server where the QoS is expected to be relatively good for various client locations. Then, it keeps the range of the server's migration within the returnable range where the server can soon come back to the averagely good location. As a result, the QoS can be always kept as good as the one under the averagely good location. Simulation results show that the proposed algorithm improves QoS of the NW-App by up to 30% compared to a greedy algorithm.