Towards the Internet of Everything: Deployment Scenarios for a QoO-aware Integration Platform

Abstract

Built upon the Internet of Things (IoT), the Internet of Everything (IoE) acknowledges the importance of data quality within sensor-based systems, alongside with people, processes and Things. Nevertheless, the impact of many technologies and paradigms that pertain to the IoE is still unknown regarding Quality of Observation (QoO). This paper proposes to study experimental results from three IoE-related deployment scenarios in order to promote the QoO notion and raise awareness about the need for characterizing observation quality within sensor-based systems. We specifically tailor the definition of QoO attributes to each use case, assessing observation accuracy within Smart Cities, observation rate for virtual sensors and observation freshness within post-disaster areas. To emulate these different experiments, we rely on a custom-developed integration platform for the assessment of QoO as a service called iQAS. We show that QoO attributes should be used to specify what is an observation of "good quality", that virtual sensors may have specific and limiting capabilities impacting QoO and that network QoS and QoO are two complementary quality dimensions that should be used together to improve the overall service provided to end-users