As a distributed deep learning paradigm, federated learning (FL) provides a powerful tool for
the accurate and efficient processing of on-board data in vehicular edge computing (VEC) …

Fog computing (FC) and Internet of Everything (IoE) are two emerging technological
paradigms that, to date, have been considered standing-alone. However, because of their …

Congestion of traffic is a key problem faced in a majority of metro cities, especially in the
developing world. Traffic congestion comprises of queues, reduced speeds, and increased …

Providing real-time cloud services to Vehicular Clients (VCs) must cope with delay and
delay-jitter issues. Fog computing is an emerging paradigm that aims at distributing small …

As vehicle applications, mobile devices and the Internet of Things are growing fast, and
developing an efficient architecture to deal with the big data in the Internet of Vehicles (IoV) …

Big data stream mobile computing is proposed as a paradigm that relies on the convergence
of broadband Internet mobile networking and real-time mobile cloud computing. It aims at …

The current energy requirements of buildings comprise a large percentage of the total
energy consumed around the world. The demand of energy, as well as the construction …

Energy efficiency has recently become a major issue in large data centers due to financial
and environmental concerns. This paper proposes an integrated energy-aware resource …

As the rise of information and communication technology, the cooperative work of vehicles
has become crucial in realizing Internet of Vehicles (IoV). Federated learning (FL) is a …

Due to the growing demand of cloud services, allocation of energy efficient resources (CPU,
memory, storage, etc.) and resources utilization are the major challenging issues of a large …