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Fog computing is an emerging computing paradigm that uses processing and storage capabilities located at the edge, in the cloud, and possibly in between. Testing and benchmarking fog applications, however, is hard since runtime…
Fog computing has emerged as a new paradigm in mobile network communications, aiming to equip the edge of the network with the computing and storing capabilities to deal with the huge amount of data and processing needs generated by the…
Hardware accelerators are available on the Cloud for enhanced analytics. Next generation Clouds aim to bring enhanced analytics using accelerators closer to user devices at the edge of the network for improving Quality-of-Service by…
A growing number of critical workflow applications leverage a streamlined edge-hub-cloud architecture, which diverges from the conventional edge computing paradigm. An edge device, in collaboration with a hub device and a cloud server,…
In recent years, the landscape of computing paradigms has witnessed a gradual yet remarkable shift from monolithic computing to distributed and decentralized paradigms such as Internet of Things (IoT), Edge, Fog, Cloud, and Serverless. The…
Fog computing becomes a promising technology to process user's requests near the proximity of users to reduce response time for latency-sensitive requests. Despite its advantages, the properties such as resource heterogeneity and…
With constrained resources, what, where, and how to cache at the edge is one of the key challenges for edge computing systems. The cached items include not only the application data contents but also the local caching of edge services that…
This article gives an overview of what Fog computing is, its uses and the comparison between Fog computing and Cloud computing. Cloud is performing well in todays World and boosting the ability to use the internet more than ever. Cloud…
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…
With the rapid development of smart manufacturing, edge computing-oriented microservice platforms are emerging as an important part of production control. In the containerized deployment of microservices, layer sharing can reduce the huge…
Edge computing operates between the cloud and end users and strives to provide low-latency computing services for simultaneous users. Redundant use of multiple edge nodes can reduce latency, as edge systems often operate in uncertain…
With the increasing use of RDF graphs, storing and querying such data using SPARQL remains a critical problem. Current mainstream solutions rely on cloud-based data management architectures, but often suffer from performance bottlenecks in…
The cloud is a new paradigm that is paving the way for new approaches and standards. The architectural styles are evolving in response to the cloud's requirements. In recent years, microservices have emerged as the preferred architectural…
We present an Edge-as-a-Service (EaaS) platform for realising distributed cloud architectures and integrating the edge of the network in the computing ecosystem. The EaaS platform is underpinned by (i) a lightweight discovery protocol that…
The scalability and flexibility of microservice architecture have led to major changes in cloud-native application architectures. However, the complexity of managing thousands of small services written in different languages and handling…
Intending to support new emerging applications with latency requirements below what can be offered by the cloud data centers, the edge and fog computing paradigms have reared. In such systems, the real-time instant data is processed closer…
An Edge-Cloud Continuum integrates edge and cloud resources to provide a flexible and scalable infrastructure. This paradigm can minimize latency by processing data closer to the source at the edge while leveraging the vast computational…
In this paper, we consider the service caching and the computing resource allocation in edge computing (EC) enabled networks. We introduce a random service caching design considering multiple types of latency sensitive services and the base…
The heterogeneous and distributed nature of the Internet of Things (IoT) is driving the need for extremely fast and fine-grained service provisioning in 5/5+G architectures and beyond. To meet these needs, it is critical to enable efficient…
Artificial Intelligence (AI) and Internet of Things (IoT) applications are rapidly growing in today's world where they are continuously connected to the internet and process, store and exchange information among the devices and the…