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Introduction
Background and Motivation of Fog Computing
Design and Organization of the Fog Layer
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Computer Science

Fog Computing Fundamentals in the Internet-of-Things

Profile image of Behailu NegashBehailu Negash

2017, Fog Computing in the Internet of Things

https://doi.org/10.1007/978-3-319-57639-8_1
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11 pages

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Abstract

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.

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

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Resource Management and Allocation in Fog Computing
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International Journal of Advanced Research in Computer Science, 2023

Smart objects are increasingly playing a crucial role in the daily operations of both industries and individuals. These devices collect data through various apps and sensors, leading to a significant accumulation of information across various sectors. The use of smart objects has grown exponentially with the advent of the Internet of Things (IoT). This has led to a significant increase in the amount of data being generated, including both structured and unstructured data. However, there are currently no effective ways to manage this data. Despite the significant advancements made in the field of IoT, incorporating cloud computing is still facing challenges such as latency, performance, network and security concerns of computing can address the challenges faced by cloud computing in the context of the Internet of Things (IoT) by bringing the cloud closer to the edge. The primary objective of fog computing is to process and store data collected by IoT devices locally on a fog node, rather than transmitting it to a remote cloud server. This approach results in faster response times and better quality of services compared to cloud computing. Fog computing is an effective solution to enable the IoT to provide reliable and secure services to a large number of IoT customers. Fog computing allows for the management of service and resource provisioning from outside of cloud computing, closer to devices, at the edge networks, or at locations specified by Service Level Agreements (SLAs). It is not intended to replace cloud computing, but rather to enhance it by enabling computation at the edge while still providing access to cloud data centers. It covers various computing frameworks, fog computing features, a comprehensive reference architectural style of fog with its multiple levels, a comprehensive study of fog with IoT, various fog system methodologies, and a thorough evaluation of the challenges in fog computing, which also serves as a middle layer between IoT sensors or devices and cloud data centers. .

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Fog Computing Architectures: A Reference for Practitioners
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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,

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Envisioning Internet of Things using Fog Computing
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International Journal of Advanced Computer Science and Applications, 2018

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Design, Resource Management, and Evaluation of Fog Computing Systems: A Survey
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A steady increase in Internet of Things (IoT) applications needing large-scale computation and long-term storage has lead to an over-reliance on Cloud computing. The resulting network congestion in Cloud, coupled with the distance of Cloud data centres from IoT, contribute to unreliable endto-end response delay. Fog computing has been introduced as an alternative to cloud, providing low-latency service by bringing processing and storage resources to the network edge. In this survey, we sequentially present the phases required in the implementation and realization of practical fog computing systems: (1) design & dimensioning of a fog infrastructure, (2) fog resource provisioning for IoT application use and IoT resource allocation to fog, (3) installation of fog frameworks for fog resource management, and (4) evaluation of fog infrastructure through simulation & emulation. Our focus is determining the implementation aspects required to build a practical large scale fog computing infrastructure to support the general IoT landscape.

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Fog Computing and Its Role in the Internet of Things
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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

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A survey on fog computing for the Internet of Things
Luca Foschini

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Fog computing has emerged to support the requirements of IoT applications that could not be met by today's solutions. Different initiatives have been presented to drive the development of fog, and much work has been done to improve certain aspects. However, an in-depth analysis of the different solutions, detailing how they can be integrated and applied to meet specific requirements, is still required. In this work, we present a unified architectural model and a new taxonomy, by comparing a large number of solutions. Finally, we draw some conclusions and guidelines for the development of IoT applications based on fog.

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Fog Computing Architecture, Application and Resource Allocation: A Review
Dr. Rajni Aron

2021

Fog Computing, may be considered as Edge Computing which expands Cloud Computing model while improving efficiency, and lowers latency. Fog computing is used to keep up day by day growing need of IT related services with the alliance of cloud computing. Having fast development of IT, the fog computing is arising as an appealing solution for retrieval and transformation of the data related to IoT applications. This paper discusses the concept, architecture of fog computing and its implementation with the existing and new applications. Fog devices are very complex and heterogeneous. The resource allocation problem is one of the core challenges in running the IoT application in the Fog area. The goal of this paper is to examine recent work on the allocation of resources in the fog area. The rationale of this survey is to realize the application of fog computing and make some improvements in the existing technology. This study will help researchers to understand and utilize technology be...

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The fog computing for internet of things: review, characteristics and challenges, and open issues
beei iaes

Bulletin of Electrical Engineering and Informatics

The internet of things (IoT) research envisions a world in which common place objects are linked to the internet and trade, store, process, and gather data from their surroundings. Due to their inherent resource limitations, IoT devices are typically unable to directly host application services, despite their increasing importance for facilitating the supply of data to enable electronic services. Since it can survive and work in tandem with centralized cloud systems and extends the latter toward the network edge, fog computing (FC) may be an appropriate paradigm to get around these restrictions. This paper reviews the overview of the IoT in terms of application and design parameters and FC. Meanwhile, this paper presents the architecture of fog computing for IoT (FC-IoT) in terms of communication, security, data quality, sensing and actuation management, codification, analysis, and decision-making. Additionally, this review provides several characteristics and challenges of FC-IoT. Finally, open issues for this paper have been discussed. This is an open access article under the CC BY-SA license.

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Need to use Fog Computing with IoT
Tajinder Kaur

International Journal of Scientific Research in Computer Science, Engineering and Information Technology

The field of computing has covered a long path. From Mainframes to traditional desktop and then towards Ubiquitous Computing. Ubiquitous Computing combined with wireless Network embedded with cloud computing have given rise to new type of concept known as Internet of Things. But this is not the final destination. A new edge is added further to this which is known as Edge Computing or Fog Computing. With less maintenance and cost based on service usage, cloud computing’s layered architecture allows the client to purchase services at different levels such as IaaS, PaaS and SaaS. It permits location independence facility as users can access these services anywhere with an internet connection and a web browser. IoT devices generate data constantly, and often analysis must be very rapid. Main sources of this huge amount of data are devices, sensors or actuators. Handling the volume, variety, and velocity of IoT data requires a new computing model. Also the time it takes to makes its way ...

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Fog Computing: A Comprehensive Architectural Survey
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Fog computing is an emerging technology to address computing and networking bottlenecks in large scale deployment of IoT applications. It is a promising complementary computing paradigm to cloud computing where computational, networking, storage and acceleration elements are deployed at the edge and network layers in a multi-tier, distributed and possibly cooperative manner. These elements may be virtualized computing functions placed at edge devices or network elements on demand, realizing the "computing everywhere" concept. To put the current research in perspective, this paper provides an inclusive taxonomy for architectural, algorithmic and technologic aspects of fog computing. The computing paradigms and their architectural distinctions, including cloud, edge, mobile edge and fog computing are subsequently reviewed. Practical deployment of fog computing includes a number of different aspects such as system design, application design, software implementation, security, computing resource management and networking. A comprehensive survey of all these aspects from the architectural point of view is covered. Current reference architectures and major application-specific architectures describing their salient features and distinctions in the context of fog computing are explored. Base architectures for application, software, security, computing resource management and networking are presented and are evaluated using a proposed maturity model. Cloud Computing, Edge Computing, Fog Computing, Internet of Things (IoT), Advanced Internet Architecture I. INTRODUCTION A S virtualization technologies mature and are perva- sively adopted, multi-tenancy is becoming possible not only in high-end computing servers but also in network elements and even end-user equipment. Thus, there is a trend towards creating network and user functions as virtual functions that are outsourced for execution in utility-based computing stores. This trend is driven by the emergence of universal composability that transforms monolithic applications into composable micro-services. The tasks and the associated micro-services vary widely in their requirements, including computing resources, elasticity, interactivity, and latency. These developments have given new life to the concept of ubiquitous computing and the notion of "computing everywhere". In this new environment, each and every computing resource may be selected as the best match for some virtual functions or tasks because of location, resources IoT Object's Domain Internet MEC Provider Core Core Cloud Multi-Tier Fog Edge Cloud Small-Cell Femto-Cell Multi-Tier Cloud IoT Gataway

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An Architectural Model for Fog Computing
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The adoption of the Internet of Things raises many challenges. A variety of its applications require widespread distribution and high mobility support. In addition to low latency and real time services. To meet these challenges, the Fog Computing is arguably a suitable solution to leverage the Internet of Things with such requirements. Indeed, we believe that the nearness of Fog nodes to the edge of the network provides an environment for critical preemptive and proactive applications and services (e.g., predicting natural disasters). Thus, this paper proposes an architectural model for Fog Computing. First, it presents a middleware to abstract the underlying devices and to unify the sensed data. Second, it describes an Operational Layer intended for service presentation, management and transformation. An environment embracing such model will provide means for early data analysis, hence low latency and real time responses. In addition, to providing an ecosystem for direct collaboration between services leading to more sophisticated applications. A flood warning system exemplifies a use case scenario to illustrate the potential adaption and application of the presented model.

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