The sensor network design procedure developed by Nabil and Narasimhan (2012), which relates process economics and data reconciliation, involves the formulation of a mixed integer cone program. The solution to this problem yields the globally optimal sensor network. A branch and bound method can be used to find the global optimum; however, for systems with large numbers of variables, this approach may require a large amount of computational effort to find the solution. In this paper, a specialized branch and bound algorithm is proposed for solving the sensor network design problem, which uses certain heuristics to obtain a solution faster. One involves a low rank factorization to reduce the size of the relaxed problem. The other involves an approximation of the global lower bound for the branch and bound solution. The utility of this algorithm is demonstrated on a simple flow network, a small but realistic evaporator system, and a medium sized steam metering network. © IFAC.