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The Internet of Things (IoT) is offering unprecedented observational data that are used for managing Smart City utilities. Edge and Fog gateway devices are an integral part of IoT deployments to acquire real-time data and enact controls.…
Anomalies are common in network system monitoring. When manifested as network threats to be mitigated, service outages to be prevented, and security risks to be ameliorated, detecting such anomalous network behaviors becomes of great…
Internet of Things (IoT) aims to bring every object (e.g. smart cameras, wearable, environmental sensors, home appliances, and vehicles) online, hence generating massive amounts of data that can overwhelm storage systems and data analytics…
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…
Mobile edge computing (a.k.a. fog computing) has recently emerged to enable in-situ processing of delay-sensitive applications at the edge of mobile networks. Providing grid power supply in support of mobile edge computing, however, is…
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…
Fog data processing systems provide key abstractions to manage data and event processing in the geo-distributed and heterogeneous fog environment. The lack of standardized benchmarks for such systems, however, hinders their development and…
Machine learning (ML) tasks are becoming ubiquitous in today's network applications. Federated learning has emerged recently as a technique for training ML models at the network edge by leveraging processing capabilities across the nodes…
Edge computing is an emerging paradigm to enable low-latency applications, like mobile augmented reality, because it takes the computation on processing devices that are closer to the users. On the other hand, the need for highly scalable…
This article explores how to drive intelligent iot monitoring and control through cloud computing and machine learning. As iot and the cloud continue to generate large and diverse amounts of data as sensor devices in the network, the…
In today's era of Internet of Things (IoT), where massive amounts of data are produced by IoT and other devices, edge computing has emerged as a prominent paradigm for low-latency data processing. However, applications may have diverse…
Edge computing has evolved to be a promising avenue to enhance the system computing capability by offloading processing tasks from the cloud to edge devices. In this paper, we propose a multi-layer edge computing framework called EdgeFlow.…
As many robot automation applications increasingly rely on multi-core processing or deep-learning models, cloud computing is becoming an attractive and economically viable resource for systems that do not contain high computing power…
In multi-tiered fog computing systems, to accelerate the processing of computation-intensive tasks for real-time IoT applications, resource-limited IoT devices can offload part of their workloads to nearby fog nodes, whereafter such…
Deep Neural Networks (DNNs) have served as a catalyst in introducing a plethora of next-generation services in the era of Internet of Things (IoT), thanks to the availability of massive amounts of data collected by the objects on the edge.…
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…
We study machine learning systems for real-time industrial quality control. In many factory systems, production processes must be continuously controlled in order to maintain product quality. Especially challenging are the systems that must…
Through connecting intelligent vehicles as well as the roadside infrastructure, the perception range of vehicles can be significantly extended, and hidden objects at blind spots can be efficiently detected and avoided. To realize this,…
The Internet of Things (IoT) has become the forefront of bridging different technologies together. It brings rise to online computational services that make mundane tasks convenient. However, the volume of devices connecting to the network…
The amount of data being produced at every epoch of second is increasing every moment. Various sensors, cameras and smart gadgets produce continuous data throughout its installation. Processing and analyzing raw data at a cloud server faces…