Related papers: PON-based connectivity for fog computing
Fog computing can be used to offload computationally intensive tasks from battery powered Internet of Things (IoT) devices. Although it reduces energy required for computations in an IoT device, it uses energy for communications with the…
This paper investigates a fog computing-assisted multi-user simultaneous wireless information and power transfer (SWIPT) network, where multiple sensors with power splitting (PS) receiver architectures receive information and harvest energy…
Fog computing was designed to support the specific needs of latency-critical applications such as augmented reality, and IoT applications which produce massive volumes of data that are impractical to send to faraway cloud data centers for…
In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a great extent. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new…
Due to the emergence of new paradigms and services such as 5G/6G, IoT, and more, current deployed wired Data Center Networks (DCNs) are not meeting the required performance metrics due to their limited reconfigurability, scalability, and…
In this survey, we discuss the evolution of distributed computing from the utility computing to the fog computing, various research challenges for the development of fog computing environments, the current status on fog computing research…
Today, wearable internet-of-things (wIoT) devices continuously flood the cloud data centers at an enormous rate. This increases a demand to deploy an edge infrastructure for computing, intelligence, and storage close to the users. The…
Edge computing has emerged as a paradigm to bring low-latency and bandwidth-intensive applications close to end-users. However, edge computing platforms still face challenges related to resource constraints, connectivity, and security. We…
The pervasiveness of "Internet-of-Things" in our daily life has led to a recent surge in fog computing, encompassing a collaboration of cloud computing and edge intelligence. To that effect, deep learning has been a major driving force…
Recent developments in the Internet of Things (IoT) and real-time applications, have led to the unprecedented growth in the connected devices and their generated data. Traditionally, this sensor data is transferred and processed at the…
Soon after realizing that Cloud Computing could indeed help several industries overcome classical product-centric approaches in favor of more affordable service-oriented business models, we are witnessing the rise of a new disruptive…
Motivated by applications such as on-device collaborative neural network inference, this work investigates edge-facilitated collaborative fog computing - in which edge-devices collaborate with each other and with the edge of the network to…
The Internet of Things (IoT) requires a new processing paradigm that inherits the scalability of the cloud while minimizing network latency using resources closer to the network edge. Building up such flexibility within the edge-to-cloud…
With the rapid growth of the Internet of Things (IoT) and a wide range of mobile devices, the conventional cloud computing paradigm faces significant challenges (high latency, bandwidth cost, etc.). Motivated by those constraints and…
While the success of edge and fog computing increased with the proliferation of the Internet of Things (IoT) solutions, such novel computing paradigm, that moves compute resources closer to the source of data and services, must address many…
Industrial Fog computing deploys various industrial services, such as automatic monitoring/control and imminent failure detection, at the Fog Nodes (FNs) to improve the performance of industrial systems. Much effort has been made in the…
Massive amounts of data are expected to be generated by the billions of objects that form the Internet of Things (IoT). A variety of automated services such as monitoring will largely depend on the use of different Machine Learning (ML)…
Industry 4.0 operates based on IoT devices, sensors, and actuators, transforming the use of computing resources and software solutions in diverse sectors. Various Industry 4.0 latency-sensitive applications function based on machine…
In order to make Internet connections ubiquitous and autonomous in our daily lives, maximizing the utilization of radio resources and social information is one of the major research topics in future mobile communication technologies. Fog…
Optical wireless communication (OWC) is a promising technology that can provide high data rates while supporting multiple users. The Optical Wireless (OW) physical layer has been researched extensively, however less work was devoted to…