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Abstract
Uncertainty in dense heterogeneous IoT sensor networks can be decreased by applying reputation-inspired algorithms, such as the EWMA (Exponentially Weighted Moving Average) algorithm, which is widely used in social networks. Despite its popularity, the eventual convergence of this algorithm for the purpose of IoT networks has not been widely studied, and results of simulations are often taken in lieu of the more rigorous proof. Therefore the question remains, whether under stable conditions, in realistic situations found in IoT networks, this algorithm indeed converges. This paper demonstrates proof of the eventual convergence of the EWMA algorithm. The proof consists of two steps: it models the sensor network as the UOG (Uniform Opinion Graph) that enables the analytical approach to the problem, and then offers the mathematical proof of eventual convergence, using formalizations identified in the previous step. The paper demonstrates that the EWMA algorithm converges under all realistic conditions.
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Authors (3)
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Piotr Cofta dr hab. inż.
- Wyższa Szkoła Bankowa w Gdańsku
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Cezary Orłowski prof. dr hab. inż.
- Wyższa Szkoła Bankowa w Gdańsku
Cite as
Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.3390/s21186211
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Keywords
Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
SENSORS
no. 21,
ISSN: 1424-8220 - Language:
- English
- Publication year:
- 2021
- Bibliographic description:
- Lebiedź J., Cofta P., Orłowski C.: Eventual Convergence of the Reputation-Based Algorithm in IoT Sensor Networks// SENSORS -Vol. 21,iss. 18 (2021), s.6211-
- DOI:
- Digital Object Identifier (open in new tab) 10.3390/s21186211
- Verified by:
- Gdańsk University of Technology
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