Related papers: Distributed Edge Analytics in Edge-Fog-Cloud Conti…
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…
Recent developments in the Internet of Things (IoT) and real-time applications, have led to the unprecedented growth in the connected devices and their generated data. Traditionally, this sensor data is transferred and processed at the…
Edge technology aims to bring Cloud resources (specifically, the compute, storage, and network) to the closed proximity of the Edge devices, i.e., smart devices where the data are produced and consumed. Embedding computing and application…
The advancements in the use of Internet of Things (IoT) devices is increasing continuously and generating huge amounts of data in a fast manner. Cloud computing is an important paradigm which processes and manages user data effectively.…
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 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…
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…
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…
In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a great extent. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new…
The Internet of Everything (IoE) solutions gradually bring every object online, and processing data in centralized cloud does not scale to requirements of such environment. This is because, there are applications such as health monitoring…
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…
The rise in embedded and IoT device usage comes with an increase in LTE usage as well. About 70\% of an estimated 18 billion IoT devices will be using cellular LTE networks for efficient connections. This introduces several challenges such…
There is an exponential growth of connected Internet of Things (IoT) devices. These have given rise to applications that rely on real time data to make critical decisions quickly. Enterprises today are adopting cloud at a rapid pace. There…
The escalating influx of data generated by networked edge devices, coupled with the growing awareness of data privacy, has restricted the traditional data analytics workflow, where the edge data are gathered by a centralized server to be…
The Internet of Things (IoT) paradigm is being rapidly adopted for the creation of smart environments in various domains. The IoT-enabled Cyber-Physical Systems (CPSs) associated with smart city, healthcare, Industry 4.0 and Agtech handle a…
Distributed fog and edge applications communicate over unreliable networks and are subject to high communication delays. This makes using existing distributed coordination technologies from cloud applications infeasible, as they are built…
Contrary to using distant and centralized cloud data center resources, employing decentralized resources at the edge of a network for processing data closer to user devices, such as smartphones and tablets, is an upcoming computing…
As we are moving towards the Internet of Things (IoT) era, the number of connected physical devices is increasing at a rapid pace. Mobile edge computing is emerging to handle the sheer volume of produced data and reach the latency demand of…
With rapid technological advancements within the domain of Internet of Things (IoT), strong trends have emerged which indicate a rapid growth in the number of smart devices connected to IoT networks and this growth cannot be supported by…
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…