相关论文: Serverless data pipeline approaches for IoT data i…

To address the increased latency, network load and compromised privacy issues associated with the Cloud-centric IoT applications, fog computing has emerged. Fog computing utilizes the proximal computational and storage devices, for sensor…

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 offers increased performance and efficiency for Industrial Internet of Things (IIoT) applications through distributed data processing in nearby proximity to sensors. Given resource constraints and their contentious use in IoT…

Internet of Things (IoT) is leading to the pervasive availability of streaming data about the physical world, coupled with edge computing infrastructure deployed as part of smart cities and 5G rollout. These constrained, less reliable but…

DNN-based video analytics have empowered many new applications (e.g., automated retail). Meanwhile, the proliferation of fog devices provides developers with more design options to improve performance and save cost. To the best of our…

IoT paradigm exploits the Cloud Computing platform to extend its scope and service provisioning capabilities. However, due to the location of the underlying IoT devices which is far away from the cloud, some services cannot tolerate the…

The IoT area has grown significantly in the last few years and is expected to reach a gigantic amount of 50 billion devices by 2020. The appearance of serverless architectures, specifically highlighting FaaS, raises the question of the of…

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…

In IoT data processing, cloud computing alone does not suffice due to latency constraints, bandwidth limitations, and privacy concerns. By introducing intermediary nodes closer to the edge of the network that offer compute services in…

The exponential growth of Internet of Things (IoT) has given rise to a new wave of edge computing due to the need to process data on the edge, closer to where it is being produced and attempting to move away from a cloud-centric…

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…

IoT applications usually rely on cloud computing services to perform data analysis such as filtering, aggregation, classification, pattern detection, and prediction. When applied to specific domains, the IoT needs to deal with unique…

The Internet of Moving Things (IoMT) requires support for a data life cycle process ranging from sorting, cleaning and monitoring data streams to more complex tasks such as querying, aggregation, and analytics. Current solutions for stream…

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…

Fog computing can support IoT services with fast response time and low bandwidth usage by moving computation from the cloud to edge devices. However, existing fog computing frameworks have limited flexibility to support dynamic service…

Abstract--- With the rapid growth of the Internet of Things (IoT), current Cloud systems face various drawbacks such as lack of mobility support, location-awareness, geo-distribution, high latency, as well as cyber threats. Fog/Edge…

The fast growth of Internet-connected embedded devices demands for new capabilities at the network edge. These new capabilities are local processing, efficient communications, and resource virtualization. The current work aims to address…

We propose a novel integrated fog cloud IoT (IFCIoT) architectural paradigm that promises increased performance, energy efficiency, reduced latency, quicker response time, scalability, and better localized accuracy for future IoT…

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…