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The deadband algorithms are implemented inside industrial gateways to reduce the volume of data sent across
different networks. Tuning the deadband sam- pling resolution by the preset interval, it is possible to estimate
a balance between the traffic rate of networks connected by industrial SCADA gateways. This work describes
the design and implementation of two original deadband algorithms based on statistical concepts derived by
the John Bollinger financial technical analysis. The statistical algorithms proposed don’t require the setup of
a preset interval while it is required by the non-statistical algorithms. The evaluation and the comparison
of all algorithms were developed by computing the effectiveness and the fidelity of a public collection of
random signals that were sampled before crossing the gateways and then, analyzed by the reported samples.
The overall performance measured in the simulations showed better results in effectiveness and fidelity for
the statistical algorithms while the mea- sured computing resources are not as good in efficiency as the
non-statistical deadband algorithms.