Today, cloud computation offloading may not be an appropriate solution for delay-sensitive
applications due to the long distance between end-devices and remote datacenters. In …

From a future perspective and with the current advancements in technology, deep
reinforcement learning (DRL) is set to play an important role in several areas like …

Smart applications and intelligent systems are being developed that are self‐reliant,
adaptive, and knowledge‐based in nature. Emergency and disaster management …

The realm of cloud computing has revolutionized access to cloud resources and their
utilization and applications over the Internet. However, deploying cloud computing for delay …

Conserving energy resources and enhancing computation capability have been the key
design challenges in the era of the Internet of Things (IoT). The recent development of …

Due to the explosive growth of the Internet of things (IoT) devices and the emergence of
diverse new applications, network traffic volume is growing exponentially. The traditional …

Embodied vision-based real-world systems, such as mobile robots, require a careful
balance between energy consumption, compute latency, and safety constraints to optimize …

The integration of edge computing with Digital Twins (DTs) has been instrumental in driving
substantial advancements in the Internet of Vehicles (IoV) domain in recent times …

Optimizing computational offloading in Mobile Edge Computing (MEC) environments
presents a multifaceted challenge requiring innovative solutions. Soft computing, recognized …

Due to the speedy development of mobile communication devices, the traditional cloudlet
computing networks struggle to manipulate the huge collected data from these devices …