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The rise of Internet of Things (IoT) devices has led to the development of numerous time-sensitive applications that require quick responses and low latency. Fog computing has emerged as a solution for processing these IoT applications, but…
The Internet of Things needs for computing power and storage are expected to remain on the rise in the next decade. Consequently, the amount of data generated by devices at the edge of the network will also grow. While cloud computing has…
Serverless computing is becoming widely adopted among cloud providers, thus making increasingly popular the Function-as-a-Service (FaaS) programming model, where the developers realize services by packaging sequences of stateless function…
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 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…
Fog computing, which distributes computing resources to multiple locations between the Internet of Things (IoT) devices and the cloud, is attracting considerable attention from academia and industry. Yet, despite the excitement about the…
With the Internet of Things (IoT) becoming a major component of our daily life, understanding how to improve the quality of service (QoS) for IoT applications through fog computing is becoming an important problem. In this paper, we…
Fog computing is an architecture that is used to distribute resources such as computing, storage, and memory closer to end-user to improve applications and service deployment. The idea behind fog computing is to improve cloud computing and…
The rapid growth of the Internet of Things (IoT) applications inflicts high requirements for computing resources and network bandwidth. A growing number of service providers are applying edge-cloud computing to improve the quality of their…
The rapid deployment of Internet of Things (IoT) applications leads to massive data that need to be processed. These IoT applications have specific communication requirements on latency and bandwidth, and present new features on their…
The emerging Fog paradigm has been attracting increasing interests from both academia and industry, due to the low-latency, resilient, and cost-effective services it can provide. Many Fog applications such as video mining and event…
The increasing use of Internet of Things (IoT) devices generates a greater demand for data transfers and puts increased pressure on networks. Additionally, connectivity to cloud services can be costly and inefficient. Fog computing provides…
Fog computing is an emerging computing paradigm which is mainly suitable for time-sensitive and real-time Internet of Things (IoT) applications. Academia and industries are focusing on the exploration of various aspects of Fog computing for…
Cloud computing revolutionized the information technology (IT) industry by offering dynamic and infinite scaling, on-demand resources and utility-oriented usage. However, recent changes in user traffic and requirements have exposed the…
Graph Neural Networks (GNNs) have gained growing interest in miscellaneous applications owing to their outstanding ability in extracting latent representation on graph structures. To render GNN-based service for IoT-driven smart…
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…
Fog computing is of particular interest to Internet of Things (IoT), where inexpensive simple devices can offload their computation tasks to nearby Fog Nodes. Online scheduling in such fog networks is challenging due to stochastic network…
This paper addresses the escalating challenges posed by the ever-increasing data volume, velocity, and the demand for low-latency applications, driven by the proliferation of smart devices and Internet of Things (IoT) applications. To…
Cloud computing, despite its inherent advantages (e.g., resource efficiency) still faces several challenges. the wide are network used to connect the cloud to end-users could cause high latency, which may not be tolerable for some…
Data-intensive applications are growing at an increasing rate and there is a growing need to solve scalability and high-performance issues in them. By the advent of Cloud computing paradigm, it became possible to harness remote resources to…