Processing big data generated in large Internet of Things (IoT) networks is challenging
current techniques. To date, a lot of network clustering approaches have been proposed to …

Load balancing is directly associated with the overall performance of a parallel and
distributed computing system. Although the relevant problems in communication and …

The Internet of Things (IoT) realizes the interconnection of different paradigms in information
technologies along with their connectivity. With its evolution, the cost and energy efficiency …

The key impediments to deploying deep neural networks (DNNs) in Internet of Things (IoT)
edge environments lie in the gap between the expensive DNN computation and the limited …

Development of internet of things (IoT) and smart devices eased life by offering numerous
applications targeting to provide real-time low latency services, but they also brought …

Enabling data processing at the network edge, as close to the actual source of data as
possible, is a challenging, yet realistic goal to be achieved by the Internet of Things (IoT) …

Internet of Things has emerged as a revolutionary technology that holds promise in a wide
range of applications. However, its deployment presents some difficulties since IoT networks …

New applications such as smart homes, autonomous vehicles are leading an increasing
research topic of convolutional neural network (CNN) based inference on IoT edge devices …

Edge computing is a new paradigm enabling intelligent applications for the Internet of
Things (IoT) using mobile, low-cost IoT devices embedded with data analytics. Due to the …

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc
networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over …