In large-scale, heterogeneous information systems, mediators are widely used for query processing and the good operation of a system strongly depends on the way the mediator allocates queries. On the other hand, it is well known that a single mediator is a potential scalability and performance bottleneck as well as a single point of failure. Thus, multiple mediators should perform the query allocation process. This task is challenging in large-scale systems because participants typically have special interests that are not performance-related. Mediators should satisfy participants interests as if there was a single mediator in the system -- i.e., with no, or almost no, additional network traffic. In this paper, we propose a virtual money-based query allocation method, called VM b QA, to perform query allocation in the presence of multiple mediators and autonomous participants. A key feature of VM b QA is that it allows a system to scale up to several mediators with no additional network cost. The results show that VM b QA significantly outperforms baseline methods from both satisfaction and performance points of view.