Statistical Deadband: A Novel Approach for Event-Based Data Reporting
Center of Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo (SP) 09606-045, Brazil
Received: 5 December 2018 / Revised: 11 January 2019 / Accepted: 15 January 2019 / Published: 18 January 2019
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Deadband algorithms are implemented inside industrial gateways to reduce the volume of data sent across different networks. By tuning the deadband sampling resolution by a preset interval
, it is possible to estimate the balance between the traffic rates 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 John Bollinger in his financial technical analysis. The statistical algorithms proposed do not require the setup of a preset interval—this is required by non-statistical algorithms. All algorithms were evaluated and compared by computing the effectiveness and fidelity over a public collection of random pseudo-periodic signals. The overall performance measured in the simulations showed better results, in terms of effectiveness and fidelity, for the statistical algorithms, while the measured computing resources were not as efficient as for the non-statistical deadband algorithms.
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MDPI and ACS Style
Torrisi, N.M. Statistical Deadband: A Novel Approach for Event-Based Data Reporting. Informatics 2019, 6, 5.
Torrisi NM. Statistical Deadband: A Novel Approach for Event-Based Data Reporting. Informatics. 2019; 6(1):5.
Torrisi, Nunzio M. 2019. "Statistical Deadband: A Novel Approach for Event-Based Data Reporting." Informatics 6, no. 1: 5.
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