Big Sensed Data Challenges in the Internet of Things

Abstract

Internet of Things (IoT) systems are inherently built on data gathered from heterogeneous sources. In the quest to gather more data for better analytics, many IoT systems are instigating significant challenges. First, the sheer volume and velocity of data generated by IoT systems are burdening our networking infrastructure, especially at the edge. The mobility and intermittent connectivity of edge IoT nodes are further hampering real-time access and reporting of IoT data. As we attempt to synergize IoT systems to leverage resource discovery and remedy some of these challenges, the rising challenges of Quality of Information (QoI) and Quality of Resource (QoR) calibration, render many IoT interoperability attempts far-fetched. We survey a number of challenges in realizing IoT interoperability, and advocate for a uniform view of data management in IoT systems. We delve into three planes that encompass Big Sensed Data (BSD) research directions, presenting a building block for future research efforts in IoT data management.