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Decision Making in IoT Systems Based on Guided Self-Organization and Autonomic Computing in the Context of the I4.0 Era

Decision Making in IoT Systems Based on Guided Self-Organization and Autonomic Computing in the Context of the I4.0 Era
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Author(s): Luis Eduardo Villela Zavala (Cinvestav Unidad Guadalajara, Mexico) and Mario Siller (Cinvestav Unidad Guadalajara, Mexico)
Copyright: 2021
Pages: 31
Source title: Decision Support Systems and Industrial IoT in Smart Grid, Factories, and Cities
Source Author(s)/Editor(s): Ismail Butun (Chalmers University of Technology, Sweden & Konya Food and Agriculture University, Turkey & Royal University of Technology, Sweden)
DOI: 10.4018/978-1-7998-7468-3.ch010



Internet of things (IoT) systems are taking an important role in daily life. Each year the number of connected devices increases considerably, and it is important to keep systems working appropriately. There are some options related to decision support systems to perform IoT systems tasks such as deployment, maintenance, and its operation on environments full of different connected devices and IoT systems interacting among them. For the decision-making process, the authors consider the complexity nature observed in IoT systems and their operational context and environments. In this sense, rather than using grain and fixed control rules/laws for the system design, the use of general principles, goals, and objectives are defined to guide the system adaptation. This has been referred to as guided self-organization (GSO) in the literature. The GSO design approach is based in evaluating the system entropy to reduce the emergence and enable self-organization. Also, in this chapter, a series of study cases from different IoT application domains are presented.

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