The objective of query optimizers is to select a good execution plan for a given query. In a distributed system, it is crucial for a query optimizer to have effective remote cost estimation in order to make a satisfactory decision. There are two categories of cost estimation models: static cost model and dynamic cost model. Unfortunately, these models suffer from several limitations. First, the static cost model is not capable of reflecting real-time situations. Second, dynamic cost model is not scalable due to its extensive probe queries. Third, these models are not designed for ad-hoc systems such as P2P, since the dynamism of peers is not taken into consideration. In this paper, we firstly propose a progressive “push-based” remote cost monitoring approach. We derive a generic static cost model from conventional static approach. Agents will be sent to remote hosts with a generic cost model and epsilons (ε) indicating magnitude of cost change, i.e., percentage of coefficient chan...