LE-STREAM is a framework for IoT data stream processing. Data processing in IoT is
challenging due to its dynamic and heterogeneous nature, and the massive amount of …

Edge devices are usually limited in resources. They often send data to the cloud, where
techniques such as filtering, aggregation, classification, pattern detection, and prediction are …

Summary The Internet of Things is underpinned by the global penetration of network‐
connected smart devices continuously generating extreme amounts of raw data to be …

The Internet of Things (IoT) extends traditional cyber-physical systems by linking sensor
based edge devices to network accessible services and resources. In most current IoT …

Due to the proliferation of the Internet of Things (IoT) paradigm, the number of devices
connected to the Internet is growing. These devices are generating unprecedented amounts …

Many Internet of Things (IoT) applications are time-critical and dynamically changing.
However, traditional data processing systems (eg, stream processing systems, cloud-based …

A key challenge for smart city analytics is fast extraction, accumulation and processing of
sensor data collected from a large number of IoT devices. Edge computing has enabled …

With the rapid growth of IoT devices, the traditional cloud computing scheme is inefficient for
many IoT based applications, mainly due to network data flood, long latency, and privacy …

Edge microservice applications are becoming a viable solution for the execution of real-time
IoT analytics, due to their rapid response and reduced latency. With Edge Computing, unlike …

Summary The Internet of Things (IoT) is an emerging technology paradigm where millions of
sensors and actuators help monitor and manage physical, environmental, and human …