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The full realization of smart city technology is dependent on the secure and honest collaboration between IoT applications and edge-computing. In particular, resource constrained IoT devices may rely on fog-computing to alleviate the…
Fog or Edge computing has recently attracted broad attention from both industry and academia. It is deemed as a paradigm shift from the current centralized cloud computing model and could potentially bring a "Fog-IoT" architecture that…
Networked embedded systems endowed with sensing, computing, control and communication capabilities allow the development of various application scenarios and represent the building blocks of the Internet of Things (IoT) paradigm.…
The evolution of smart cities demands scalable, secure, and energy-efficient architectures for real-time data processing. With the number of IoT devices expected to exceed 40 billion by 2030, traditional cloud-based systems are increasingly…
Fog Computing is now emerging as the dominating paradigm bridging the compute and connectivity gap between sensing devices (a.k.a. "things") and latency-sensitive services. However, as fog deployments scale by accumulating numerous devices…
We consider a detection problem where sensors experience noisy measurements and intermittent communication opportunities to a centralized fusion center (or cloud). The objective of the problem is to arrive at the correct estimate of event…
Mobile users in an urban environment access content on the internet from different locations. It is challenging for the current service providers to cope with the increasing content demand from a large number of collocated mobile users.…
Industry 4.0 applications foster new business opportunities but they also pose new and challenging requirements, such as low latency communications and highly reliable systems. They enable to exploit novel wireless technologies (5G), but it…
In recent years, there has been a shift in computing architectures, moving away from centralized cloud computing towards decentralized edge and fog computing. This shift is driven by factors such as the increasing volume of data generated…
The evolution of the utilization of technologies in nearly all aspects of life has produced an enormous amount of data essential in a smart city. Therefore, maximizing the benefits of technologies such as cloud computing, fog computing, and…
Machine Learning systems rely on data for training, input and ongoing feedback and validation. Data in the field can come from varied sources, often anonymous or unknown to the ultimate users of the data. Whenever data is sourced and used,…
In big cloud structures or large data structures, fog computing could be interpreted, referring critically to the growing issues and problems in accessing the information among the Internet of things (IoT) devices. Fog computing can be used…
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…
Social sensing services use humans as sensor carriers, sensor operators and sensors themselves in order to provide situation-awareness to applications. This promises to provide a multitude of benefits to the users, for example in the…
Emerging technologies that generate a huge amount of data such as the Internet of Things (IoT) services need latency aware computing platforms to support time-critical applications. Due to the on-demand services and scalability features of…
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…
Nowadays, the Internet of Things (IoT) creates a vast ecosystem of intelligent objects interconnected via the Internet, allowing them to exchange information and to interact. This paradigm has been extended to a new concept, called the Web…
Due to the pervasive diffusion of personal mobile and IoT devices, many "smart environments" (e.g., smart cities and smart factories) will be, generators of huge amounts of data. Currently, analysis of this data is typically achieved…
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…
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…