In the Internet of Vehicles (IoV), Federated Learning (FL) provides a privacy-preserving
solution by aggregating local models without sharing data. Traditional supervised learning …

Computation offloading via device-to-device communications can improve the performance
of mobile edge computing by exploiting the computing resources of user devices. However …

Sustainable resource management within a cloud computing environment is a highly critical
and prominently studied research topic. In this context, this paper presented a …

To enable resource-constrained wireless devices (WDs) to process the computation-
intensive and latency-sensitive computation tasks, the wireless powered mobile edge …

The Hadoop distributed file system (HDFS) effectively manages data by segmenting it into
blocks distributed across DataNodes in its cluster. While default block sizes in Hadoop 2. x …

Mobile edge computing emerges to serve mobile users with low-latency computation
offloading in edge networks, which are resource-constrained with massive users and …

Edge computing and container technologies offer more possibilities for the development of
Internet of Vehicles (IOV). However, many studies have neglected the dependencies among …

We consider the problem of dependent task offloading in edge computing with unknown
system-side information (eg, edge transmission rate and computation resources). In this …

At a significant moment in the rapid development of cloud technology, large-scale cloud
computing centers have emerged. With the emergence of the internet and artificial …

Current edge computing (EC) solutions face the significant challenge of limited
computational capacities. Effectively allocating resources and controlling the system to …