Though capillary sensor networks have the advantage of reporting punctual estimations of their sensed quantity, it is often useful for the nodes to know the overall average value of the same quantity. This is required, for example, when the network can make autonomous decisions. Several algorithms exist for solving the averaging problem in a distributed manner. Their efficiency can be measured by the number of iterations needed to converge to the average sensed value. In this paper, we consider two point-topoint and one point-to-multipoint distributed averaging algorithms that can be seen as variants of the same averaging solution. We define a set of analytical tools to evaluate the performance of these algorithms and to optimize their parameters in such a way to accelerate convergence. We also provide a performance assessment, based on numerical simulations, aimed at verifying the results of the analytical treatment and at comparing the considered schemes.