Resource allocation and offloading in green Internet of Things (IoT) relies on the multi-level
heterogeneous platforms. The energy expenses of the platform determine the reliability of …

In order to effectively extend the lifetime of Internet of Things (IoT) devices, improve the
energy efficiency of task processing, and build a self‐sustaining and green edge computing …

Cloud computing has become the de facto computing platform for application processing in
the era of the Internet of Things (IoT). However, limitations of the cloud model, such as the …

To fulfill people's expectations for smart and user-friendly Internet of Things (IoT)
applications, the quantity of processing is fast expanding, and task latency constraints are …

Serverless architecture enables various intelligent applications to be run without managing
infrastructure. In this architecture, the computing cost is generally proportional to the number …

In the distributed task offloading system, the desired task completion time cannot be
achieved when lots of mobile devices offload simultaneously the tasks with high complexity …

The edge computing paradigm is evolving to provide time-sensitive computing services for
energy-constrained mobile IoT devices, with the purpose of decreasing latency. In this …

Internet of Things (IoT) and mobile edge computing (MEC) architectures are common in real-
time application scenarios for improving the reliability of service responses. Energy …

The integration of Edge Computing (EC) and Energy Harvesting (EH) technologies has
facilitated the growth of the Internet of Things (IoT), allowing for the interconnectivity of a …

Offloading assists in overcoming the resource constraints of specific elements, making it one
of the primary technical enablers of the Internet of Things (IoT). IoT devices with low battery …