The arising Internet of Things (IoT) will require significant changes to current stream
processing engines (SPEs) to enable large-scale IoT applications. In this paper, we present …

The Internet of Things (IoT) has created new and challenging opportunities for data
analytics. The IoT represents an infinitive source of massive and heterogeneous data …

The Internet of Things (IoT) adoption grows significantly and is successful in many different
domains. Nevertheless, the ever-growing demand for more connected devices pushes the …

Over the last years, many Internet of Things (IoT) platforms have been developed to manage
data from public and industrial environmental settings. To handle the upcoming amounts of …

The new standard oneM2M (one machine-to-machine) aims to standardize the architecture
and protocols of Internet of Things (IoT) middleware for better interoperability. Although the …

As smart environments move from a research vision to concrete manifestations in real-world
enabled by the Internet of Things, they are encountering a number of very practical …

Data management systems will face several new challenges in supporting IoT applications
during the coming years. These challenges arise from managing large numbers of …

Newly arising IoT-driven use cases often require low-latency anaiytics to derive time-
sensitive actions, where a centralized cloud approach is not applicable. An emerging …

Massive amount of IoT data poses unique challenges in centralized data management
systems. Specifically, IoT data can originate from heterogeneous and distributed sources …