The ever-increasing spread of Internet of Things (IoT)-based technologies paired with the diffusion of the edge-based computing boosts the development of pervasive cyber ecosystems having the goal of improving the life quality of people and assisting them in daily activities. In this context, cognitive behaviors are purposely required to make such ecosystems able to adapt to people needs and to envisage their behaviors. Despite the growing interest in cognitive ecosystems, still there is a lack of methodological approaches devoted to supporting the design and implementation of such complex systems. This paper proposes ITEMa, an Iot-based smarT Ecosystem Modeling Approach based on a three-layered architecture offering some well-suited abstractions tailored to the development of IoT-based ecosystems which exhibit cognitive behaviors and are able to exploit computational resources located either at the edge of the network or in the Cloud. The effectiveness of the approach is demonstrated through a case study concerning the development of a Smart Office devoted to forecast some usual office activities and to properly adapt the office environmental conditions to them.
ITEMa: A methodological approach for cognitive edge computing IoT ecosystems
Cicirelli F;Guerrieri A;Mercuri A;Spezzano G;Vinci A
2019
Abstract
The ever-increasing spread of Internet of Things (IoT)-based technologies paired with the diffusion of the edge-based computing boosts the development of pervasive cyber ecosystems having the goal of improving the life quality of people and assisting them in daily activities. In this context, cognitive behaviors are purposely required to make such ecosystems able to adapt to people needs and to envisage their behaviors. Despite the growing interest in cognitive ecosystems, still there is a lack of methodological approaches devoted to supporting the design and implementation of such complex systems. This paper proposes ITEMa, an Iot-based smarT Ecosystem Modeling Approach based on a three-layered architecture offering some well-suited abstractions tailored to the development of IoT-based ecosystems which exhibit cognitive behaviors and are able to exploit computational resources located either at the edge of the network or in the Cloud. The effectiveness of the approach is demonstrated through a case study concerning the development of a Smart Office devoted to forecast some usual office activities and to properly adapt the office environmental conditions to them.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.