4.7 Article

Computational Models of Human Decision-Making with Application to the Internet of Everything

期刊

IEEE WIRELESS COMMUNICATIONS
卷 28, 期 1, 页码 152-159

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MWC.001.2000250

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Computational modeling; Wireless communication; Task analysis; Games; Optimization; Wireless sensor networks; Predictive models

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The concept of the Internet of Things has evolved into the Internet of Everything, incorporating things, humans, data, and processes as its pillars in a heterogeneous large-scale network. Proper modeling of human decision-making is crucial in networking applications, as humans are irrational beings that need to be taken into consideration when developing management, analysis, and optimization policies.
The concept of the Internet of Things (IoT) first appeared a few decades ago. Today, by the ubiquitous wireless connectivity, the boost of machine learning and artificial intelligence, and the advances in big data analytics, it is safe to say that IoT has evolved to a new concept called the Internet of Everything (IoE) or the Internet of All. IoE has four pillars, things, human, data, and processes, which render it as an inhomogeneous large-scale network. A crucial challenge of such a network is to develop management, analysis, and optimization policies that besides utility-maximizer machines, also take irrational humans into account. We discuss several networking applications in which appropriate modeling of human decision-making is vital. We then provide a brief review of computational models of human decision-making. Based on one such model, we develop a solution for a task offloading problem in fog computing and we analyze the implications of including humans in the loop.

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