This paper highlights humans’ social and mobility behaviors’ role in the continuous engineering of sustainable socio-technical Internet of Things (IoT) systems. Our approach relates the humans’ characteristics and intentions with the system’s goals, and models such interaction. Such a modeling approach aligns the architectural design and associated quality of service (QoS) with humans’ quality of experience (QoE). We design a simulation environment that combines agent-based social simulation (ABSS) with architectural models generated through a model-driven engineering approach. Our modeling approach facilitates choosing the best architectural model and system configuration to enhance both the humans’ and system’s sustainability. We apply our approach to the Uffizi Galleries crowd management system. Taking advantage of real data, we model scenarios related to humans’ speed, vision variations, grouping, and social attachment, which impact QoE. We then assess various architectural models with different SW/HW configurations to propose the optimal model based on different scenarios concerning QoS-QoE requirements.

Human Behavior-Oriented Architectural Design

Muccini H.;
2021

Abstract

This paper highlights humans’ social and mobility behaviors’ role in the continuous engineering of sustainable socio-technical Internet of Things (IoT) systems. Our approach relates the humans’ characteristics and intentions with the system’s goals, and models such interaction. Such a modeling approach aligns the architectural design and associated quality of service (QoS) with humans’ quality of experience (QoE). We design a simulation environment that combines agent-based social simulation (ABSS) with architectural models generated through a model-driven engineering approach. Our modeling approach facilitates choosing the best architectural model and system configuration to enhance both the humans’ and system’s sustainability. We apply our approach to the Uffizi Galleries crowd management system. Taking advantage of real data, we model scenarios related to humans’ speed, vision variations, grouping, and social attachment, which impact QoE. We then assess various architectural models with different SW/HW configurations to propose the optimal model based on different scenarios concerning QoS-QoE requirements.
978-3-030-86043-1
978-3-030-86044-8
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11697/178643
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