相关论文: MicroFog: A Framework for Scalable Placement of Mi…
The Fog computing paradigm utilises distributed, heterogeneous and resource-constrained devices at the edge of the network for efficient deployment of latency-critical and bandwidth-hungry IoT application services. Moreover, MicroService…
In the ever-evolving landscape of computing, the advent of edge and fog computing has revolutionized data processing by bringing it closer to end-users. While cloud computing offers numerous advantages, including mobility, flexibility and…
During the last decade, Cloud computing has efficiently exploited the economy of scale by providing low cost computational and storage resources over the Internet, eventually leading to consolidation of computing resources into large data…
Fog computing extends cloud computing technology to the edge of the infrastructure to let IoT applications access objects' data with reduced latency, location awareness and dynamic computation. By displacing workloads from the central cloud…
The Industry 4.0 revolution has been made possible via AI-based applications (e.g., for automation and maintenance) deployed on the serverless edge (aka fog) computing platforms at the industrial sites -- where the data is generated.…
Fog/Edge computing model allows harnessing of resources in the proximity of the Internet of Things (IoT) devices to support various types of real-time IoT applications. However, due to the mobility of users and a wide range of IoT…
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…
Edge/Fog computing is a novel computing paradigm that provides resource-limited Internet of Things (IoT) devices with scalable computing and storage resources. Compared to cloud computing, edge/fog servers have fewer resources, but they can…
The Internet of Things (IoT) paradigm is being rapidly adopted for the creation of smart environments in various domains. The IoT-enabled Cyber-Physical Systems (CPSs) associated with smart city, healthcare, Industry 4.0 and Agtech handle a…
With the rapid development of mobile communication, multimedia services have experienced explosive growth in the last few years. The high quantity of mobile users, both consuming and producing these services to and from the Cloud Computing…
Fog computing emerged as a crucial platform for the deployment of IoT applications. The complexity of such applications requires methods that handle the resource diversity and network structure of Fog devices while maximizing the service…
IoT application providers increasingly use MicroService Architecture (MSA) to develop applications that convert IoT data into valuable information. The independently deployable and scalable nature of microservices enables dynamic…
Meeting the requirements of future services with time sensitivity and handling sudden load spikes of the services in Fog computing environments are challenging tasks due to the lack of publicly available Fog nodes and their characteristics.…
In recent years, there has been a significant expansion in the Internet of Things (IoT), with a growing number of devices being connected to the internet. This has led to an increase in data collection and analysis as well as the…
Fog computing is a promising paradigm for real-time and mission-critical Internet of Things (IoT) applications. Regarding the high distribution, heterogeneity, and limitation of fog resources, applications should be placed in a distributed…
The emerging 5G paradigm will enable multi-radio smartphones to run high-rate stream applications. However, since current smartphones remain resource and battery-limited, the 5G era opens new challenges on how to actually support these…
The Internet of Things (IoT) aims to connect everyday physical objects to the internet. These objects will produce a significant amount of data. The traditional cloud computing architecture aims to process data in the cloud. As a result, a…
Fog computing aims at extending the Cloud towards the IoT so to achieve improved QoS and to empower latency-sensitive and bandwidth-hungry applications. The Fog calls for novel models and algorithms to distribute multi-service applications…
The smart grid utilizes many Internet of Things (IoT) applications to support its intelligent grid monitoring and control. The requirements of the IoT applications vary due to different tasks in the smart grid. In this paper, we propose a…
As edge and fog computing become central to modern distributed systems, there's growing interest in combining serverless architectures with privacy-preserving machine learning techniques like federated learning (FL). However, current…