An Architectural Model for Fog Computing (original) (raw)

Fog Computing Fundamentals in the Internet-of-Things

Fog Computing in the Internet of Things, 2017

The functional separation of different system components has been used to address some critical challenges in architecture design. One of the well known approaches of physical separation of functional units is in client-server architectures. The server side of this separation is hidden inside the cloud infrastructure in the case of an Internet scale system. This model is serving a wide range of applications running over the Internet providing storage, computing power, and redundant services for reliability. However, in the new paradigm of the Internet-of-Things, the traditional separation partly fails to meet the set of system requirements. Fog computing is introduced as an intermediate layer between the clients and the Cloud. It brings computing, storage, management, and network services among others, closer to the sensor/actuator nodes. This book discusses the features of Fog computing, its advantages, internal details and present case studies to demonstrate it in real application scenarios. The focus of this chapter is to give an overview of Fog computing at a higher level.

Fog Computing and Its Role in the Internet of Things

Fog Computing extends the Cloud Computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Defining characteristics of the Fog are: a) Low latency and location awareness; b) Widespread geographical distribution; c) Mobility; d) Very large number of nodes, e) Predominant role of wireless access, f) Strong presence of streaming and real time applications, g) Het-erogeneity. In this paper we argue that the above characteristics make the Fog the appropriate platform for a number of critical Internet of Things (IoT) services and appli

Fog Computing Architectures: A Reference for Practitioners

IEEE Internet of Things Magazine, 2019

Soon after realizing that Cloud Computing could indeed help several industries overcome classical product-centric approaches in favor of more affordable service-oriented business models, we are witnessing the rise of a new disruptive computing paradigm, namely Fog Computing. Essentially, Fog Computing can be considered as an evolution of Cloud Computing, in the sense that the former extends the latter to the edge of the network (that is, where the connected devices-the thingsare) without discontinuity, realizing the so-called "cloud-tothing continuum". Since its infancy, Fog Computing has been considered as a necessity within several Internet of Things (IoT) domains (one for all: Industrial IoT) and, more generally, wherever embedded artificial intelligence and/or more advanced distributed capabilities were required. Fog Computing cannot be considered only a fancy buzzword: according to separate, authoritative analyses its global market will reach $18 billion by 2022, while nearly 45% of the world's data will be moved to the network edge by 2025. In this paper, we take stock of the situation, summarizing the most modern and mature Fog Computing initiatives from standardization, commercial, and open-source communities perspectives. Index Terms-Fog Computing, Edge Computing, Cloud Computing, Embedded Artificial Intelligence, Cloud-to-Thing continuum I. INTRODUCTION The original mission of the Internet of Things (IoT) was to connect devices to the Internet, enabling communications and autonomous interactions among everyday objects. Since the beginning of the IoT era, sensing, actuation, and communications have been the main tasks of the designers and the integrators of these devices. As a matter of facts, always tinier and more powerful devices are reaching the global market at very affordable prices. However, in several modern vertical domains, applications require always more computational capabilities than those available on commercially available "smart" objects. In such cases, the classical approach is to send data to remote cloud endpoints that have, ideally, infinite computational power and storage capabilities. Here it is possible to run computational intensive operations like machine learning tasks, data aggregation, storage, monitoring, and visualization. In this respect, many M. Antonini, M. Vecchio and F. Antonelli are with the OpenIoT research unit, FBK CREATE-NET,

A Review-Fog Computing and Its Role in the Internet of Things

Fog computing extends the Cloud Computing paradigm to the edge of the network, thus enabling a new breed of applications and services. Dening characteristics of the Fog are: a) Low latency and location awareness; b) Widespread geographical distribution; c) Mobility; d) Very large number of nodes, e) Predominant role of wireless access, f) Strong presence of streaming and real time applications, g) Het-erogeneity. In this paper we argue that the above characteristics make the Fog the appropriate platform for a number of critical Internet of Things (IoT) services and applications, namely, Connected Vehicle, Smart Grid , Smart Cities, and, in general, Wireless Sensors and Actuators Networks (WSANs).

360 Deg. Overview of Fog Computing

International Journal for Research in Applied Science and Engineering Technology, 2019

Fog Computing (introduced in 2012) is now considered to be the most prioritized choice for applications of Internet of Things. Fog Computing allows to move a part of the processing in the cloud to the network devices present along the node to the cloud. It makes communications and storage services in proximity to the end user. It is used to well support time dependent, location dependent, massive scale, and latency sensitive applications. Fog computing makes the task laid-back for cloud by filtering the needless data before forwarding the data to the cloud. This paper is assembled into two parts. The first part covers the basic outline and architecture of fog. The second part talks about the working of Fog Computing and its benefits and limitations.

Envisioning Internet of Things using Fog Computing

International Journal of Advanced Computer Science and Applications, 2018

Internet of Things is the future of the Internet. It encircles a wide scope. There are currently billions of devices connected to the Internet and this trend is expecting to grow exponentially. Cisco predicts there are at present 20 billion connected devices. These devices, along with their varied data types, transmission rates and communication protocols connect to the Internet seamlessly. The futuristic implementation of Internet of Things across various scenarios demands the real time performance delivery. These range from RFID connected devices to huge data centers. Until date, there is no single communication protocol available for envisioning IoT. There is still no common, agreed upon architecture. Hence, huge challenges lie ahead. One of the ways to envision Internet of Things is to make use of Fog Networks. Fog is essentially a cloudlet, located nearer to the ground. It offers lower latency and better bandwidth conservation. The Fog or Fog computing is a recent concept. The OpenFog Consortium is a joint effort of many vendors. Its latest work is the background study for realizing Fog as a possible paltform for activating Internet of Things. This paper revolves around Envisioning Internet of Things using Fog computing. It begins with a detailed background study of Internet of Things and Fog Architecture. It covers applications and scenarios where such knowledge is highly applicable. The paper concludes by proposing Fog Computing as a possible platform for Internet of Things.

Role of Fog Computing in IoT based applications

Internet of things (IoT) services have been accepted and accredited globally for the past couple of years and have had increasing interest from researchers. Internet of Things (IoT), requires mobility support and geo-distribution in addition to location awareness and low latency. We argue that a new platform is needed to meet these requirements; a platform we call Fog

Fog computing is a novel computing paradigm

Fog computing is a novel computing paradigm that leverages the benefits of cloud computing while overcoming some of its limitations. It extends cloud computing to the edge of the network, where data is generated and consumed, and enables low-latency, location-aware, and context-aware services. In this paper, we provide an overview of fog computing, its architecture, key enabling technologies, and applications. We also discuss the challenges and open research issues in fog computing, including security, resource management, and scalability. We conclude with a discussion of future research directions in fog computing. Introduction: With the proliferation of smart devices, the amount of data generated at the edge of the network is increasing rapidly. This data is often time-sensitive and requires real-time processing and analysis. Cloud computing has been widely adopted to handle the storage and processing of this data. However, cloud computing has several limitations, such as high latency, limited bandwidth, and lack of mobility support. Fog computing, also known as edge computing, is a new computing paradigm that aims to overcome these limitations by extending cloud computing to the edge of the network. Fog Computing Architecture: Fog computing architecture consists of three layers: the edge layer, the fog layer, and the cloud layer. The edge layer includes smart devices and sensors that generate data. The fog layer includes the fog nodes, which are located closer to the edge than the cloud, and provide computing and storage resources. The cloud layer includes the data centers that provide massive computing and storage resources. Fog computing architecture is a hierarchical model that comprises three layers, namely edge, fog, and cloud layers, as described below: Edge Layer: This layer is the first layer of the fog computing architecture and comprises smart devices and sensors that generate data. The edge devices can include sensors, cameras, and other Internet of Things (IoT) devices. These devices produce a massive amount of data that requires real-time processing and analysis. The edge layer is responsible for collecting, processing, and filtering the data before sending it to the fog layer. Reference: Al-Fuqaha et al. (2015) provide a survey of the enabling technologies, protocols, and applications for IoT. They highlight the importance of edge devices in generating data and collecting sensory information.

Fog Computing Applications: Taxonomy and Requirements

ArXiv, 2019

Fog computing was designed to support the specific needs of latency-critical applications such as augmented reality, and IoT applications which produce massive volumes of data that are impractical to send to faraway cloud data centers for analysis. However this also created new opportunities for a wider range of applications which in turn impose their own requirements on future fog computing platforms. This article presents a study of a representative set of 30 fog computing applications and the requirements that a general-purpose fog computing platform should support.

Fog Computing: A Platform for Internet of Things and Analytics

Studies in Computational Intelligence, 2014

Internet of Things (IoT) brings more than an explosive proliferation of endpoints. It is disruptive in several ways. In this chapter we examine those disruptions, and propose a hierarchical distributed architecture that extends from the edge of the network to the core nicknamed Fog Computing. In particular, we pay attention to a new dimension that IoT adds to Big Data and Analytics: a massively distributed number of sources at the edge.