Mobile Edge Computing (MEC) is a viable solution in response to the growing demand for
broadband services in the new-generation heterogeneous systems. The dense deployment …

With Cloud computing becoming mainstream for the execution of various applications, the
multi-objective scheduling algorithms for providing the most suitable services to users have …

With the rapid surge in cloud services, cloud load balancing has become a paramount
research issue. The major part of a cloud computing system's operational costs is attributed …

In a cloud computing environment, tasks are divided among virtual machines (VMs) with
different start times, duration and execution periods. Thus, distributing these loads among …

Skewed data distribution leads to certain tasks or nodes handling much more data than
others, thereby slowing down their execution speed and classifying them as stragglers …

Federated learning (FL) emerges as a promising solution to train machine learning (ML)
models from distributed data sources. In FL, the heterogeneous and imbalanced data …

Efficient allocation of tasks and resources is crucial for the performance of heterogeneous
cloud computing platforms. To achieve harmony between task completion time, device …

Distributed and heterogeneous edge computing environments require efficient allocation
and scheduling of multiple users' applications. This paper presents a game-theoretic …

Nowadays, solid-state drives (SSDs) have become the best choice of storage devices
because of its brilliant advantages such as small size, low-power consumption, shake …

By providing distributed and ultra‐low‐latency communication between industrial devices
and resource components, the Industrial Internet of Things (IIoT) is at the forefront of a new …