Through intelligent integration of sensing and processing functions, the sensing technology of the future is evolving towards networks of configurable sensors acting in concert. Realizing the potential of collaborative real-time configurable sensor systems presents a number of challenges including the need to address a number of challenges including the need to address the massive global optimization problem resulting from incorporating a large array of control parameters. This paper proposes a systematic approach to addressing complex global optimization problems by constraining the problem to a set of key control parameters and recasting a mission-oriented goal into a tractable joint optimization formula. Using idealized but realistic physical models, a systematic methodology to approach complex multi-dimensional joint optimization problems is used to compute system performance bounds for dynamic sensor configurations.