Fog computing (FC), extending cloud services to the network edge, has emerged as a key
paradigm for low-latency applications like the Internet of Things (IoT). However, efficient …

Task scheduling and resource management are critical for improving system performance
and enhancing consumer satisfaction in distributed computing environments. The dynamic …

Fog computing paradigm provides diverse processing resources and storage close to the
edge of Internet of Things (IoT) networks. Workflow scheduling is an open issue in fog …

Abstract The Internet of Things (IoT) is constantly evolving. The variety of IoT applications
has caused new demands to emerge on users' part and competition between computing …

In the Internet of Things (IoT) ecosystem, some processing is done near data production
sites at higher speeds without the need for high bandwidth by combining Fog Computing …

Workflow scheduling aims to optimize task allocation and execution in cloud–fog​
computing environments. Finding an optimal algorithm for workflow scheduling poses a …

In recent years, the increasing use of the Internet of Things (IoT) has generated excessive
amounts of data. It is difficult to manage and control the volume of data used in cloud …

The rapid proliferation of low-latency and high-bandwidth applications has brought edge
computing to the forefront of mobile network architectures. However, the strategic placement …

Abstract The execution of Map-Reduce applications on the Hadoop cluster poses significant
challenges due to the non-consideration of data locality, ie, assigning tasks to compute …

A robust visual location estimation scheme in large-scale complex scenes is critical for
location-relevant Internet of Things (IoT) applications such as autonomous vehicles and …