A multimedia system utilizes a set of correlated media streams each of which partially help in achieving the system goal. However, since not all of the streams always contribute towards the goal, there is a need for determining the most informative subset from the available set of media streams at any instant. For example, a subset of two video cameras and two microphones could be better than any other subset of multimedia sensors at some time instance. This paper presents a novel framework to find the optimal subset of media streams that achieves the system goal under specified constraints. The proposed framework uses a dynamic programming approach to find the optimal subset of media streams based on two criteria; first, by maximizing the probability of achieving the goal under the specified maximum cost, and second by minimizing the cost of using the streams so that the goal is achieved with a specified minimum probability. To show the utility of our framework, we provide the simulation results for hypothesis testing.