In the Cloud of Things, data are stored and processed in the cloud and the results are sent to IoT Smart Objects (SOs) with, generally, a network latency overhead due to the distances between the cloud and the local IoT networks. Moreover, trusting inappropriate counterparts can expose SOs to threats and to mitigate them we propose a clustering reputation-based approach for IoT Edge-based platform processing and storing data on the “edge”, nearby the SOs. Whenever SOs interact for services, a feedback is sent to an Edge server to calculate their reputation scores. In this way, the reputation systems is moved from the cloud to the edge servers, but available on the cloud if a SO will change edge domain. To this aim, we designed a distributed Trusted Object Framework (TOF) where heterogeneous OSs host and exploit the assistance of associated software agents and verified its performance in a simulated scenario which confirmed the potential advantages of TOF.
Trusted Object Framework (TOF): A clustering reputation-based approach using edge computing for sharing resources among IoT smart objects
Fortino G.;Fotia L.;Sarne G. M. L.
2021-01-01
Abstract
In the Cloud of Things, data are stored and processed in the cloud and the results are sent to IoT Smart Objects (SOs) with, generally, a network latency overhead due to the distances between the cloud and the local IoT networks. Moreover, trusting inappropriate counterparts can expose SOs to threats and to mitigate them we propose a clustering reputation-based approach for IoT Edge-based platform processing and storing data on the “edge”, nearby the SOs. Whenever SOs interact for services, a feedback is sent to an Edge server to calculate their reputation scores. In this way, the reputation systems is moved from the cloud to the edge servers, but available on the cloud if a SO will change edge domain. To this aim, we designed a distributed Trusted Object Framework (TOF) where heterogeneous OSs host and exploit the assistance of associated software agents and verified its performance in a simulated scenario which confirmed the potential advantages of TOF.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.