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This work is motivated by the idea of using randomly deployed wireless networks of miniature smart sensors to serve as distributed instrumentation. In such applications, often the objective of the sensor network is to repeatedly compute and, if required, deliver to an observer some result based on the values measured at the sensors. We argue that in such applications it is important for the sensors to self-organize in a way that optimizes network throughput. We identify and discuss two main problems of optimal self-organization: (1) building an optimal topology, and (2) tuning network access parameters, such as the transmission attempt rate. We consider a simple random access model for sensor networks and formulate these problems as optimization problems. We then present centralized as well as distributed algorithms for solving them. Results show that the performance improvement is substantial and implementation of such optimal self-organization techniques may be worth the additional complexity.