This work addresses the optimization of distributed compression in a sensor network. In particular, distributed sensors measure noisy versions of the same process of interest and try to forward their measurements over capacity-limited links to a common receiver. If direct communication among sensors is not possible, this setup is widely known as the CEO problem. This work focuses on an implementation point of view to solve this problem as well as an information-theoretic analysis of the proposed algorithms.