We describe the problem of data dissemination in stream-oriented applications where the required filter is a function of the current state.We call such functions dynamic filters. A State Aware Data Dissemination Network (SA-DDN) is proposed to support dynamic filters. Two approaches Single-level Filtering (SF) and Multilevel Filter Decomposition (MFD) are proposed to facilitate the data dissemination. We show how MFD improves performance over SF. We then describe a realization of SA-DDN on top of an improved bi-directional Chord overlay with a built-in multicast mechanism. An application of stock price monitoring is implemented based on SA-DDN and real life stock quotes are collected to demonstrate the feasibility of our system. Extensive simulations are performed to compare the performance of both approaches and provide insight into the advantages of MFD.