Current federated systems deploy cost-based query optimization mechanisms; i.e., the optimizer selects a global query plan with the lowest cost to execute. Thus, cost functions influence what remote sources (i.e. equivalent data sources) to access and how federated queries are processed. In most federated systems, the underlying cost model is based on database statistics and query statements; however, the system load of remote sources and the dynamic nature of the network latency in wide area networks are not considered. As a result, federated query processing solutions can not adapt to runtime environment changes, such as network congestion or heavy workloads at remote sources. We present a novel system architecture that deploys a Query Cost Calibrator to calibrate the cost function based on system load and network latency at the remote sources and consequently indirectly "influences" query routing and load distribution in federated information systems.