" FOG COMPUTING " Focusing on Users at the Edge of Internet of Things (original) (raw)
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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
2016
The “Cloud” is considered as the powerhouse that will fuel and support the expansion of IoT. The Internet of Things (IoT) continues to gain momentum as vendors and enterprises begin to embrace the opportunities this market presents. According to new research from International Data Corporation (IDC), the worldwide Internet of Things market will grow from 655.8billionin2014to655.8 billion in 2014 to 655.8billionin2014to1.7 trillion in 2020 with a compound annual growth rate (CAGR) of 16.9% [11] with devices, connectivity and IT services taking a majority stake in the market of IoT. This emerging wave of end-computing deployment requires mobility support, geo-distribution, location awareness and most notably very low latency. Will the Cloud be able to provide these features? Or maybe, the right question to ask is if it will be able to sustain the expected growth of IoT, with billions of devices communicating over data shared across inter-clouds while providing the kind of quality of service that we have come to expect over time. In this paper, we pore over the existing Cloud Computing landscape and contemplate its place in the “Things to Come” era of computing. We look at new hierarchical distributed architectures that extend from the edge of the network to the core of the cloud and delve into the idea of extending out the cloud and bringing it to the edge of the compute endpoints. Something that is now being called “The Fog”
Fog Computing: Will it be the Future of Cloud Computing?
Cloud computing is the newest computing paradigm that makes computing resources available over the Internet on a utility costing basis. Cloud computing offers many advantages to users in terms of reduced cost, elimination of system administrative functions, increased flexibility, better reliability and location independence. Though these are definite advantages, cloud computing also suffers from certain limitations. These limitations arise from the very same reason that is considered an advantage too. Hosting of cloud data centres in the Internet creates large and unpredictable network latencies and undefined security issues as sensitive data is now entrusted to a third party. Also location independence of processing in cloud computing may also not desirable for certain types of networks such as sensor networks and Internet of Things. These services are known as location aware services and require location dependent fast processing. In order to overcome these limitations, researchers have proposed a new cloud computing model called fog computing where the cloud system is located either at the edge of the private network or very close to it. In this paper, the authors take an in depth look at both these technologies to investiga te fog computing can reliably overcome the limitations of cloud computing and effectively replace it and become the de facto cloud computing model of the future.
Distributing Computing in the Internet of Things: Cloud, Fog and Edge Computing Overview
NEO 2016
The main postulate of the Internet of things (IoT) is that everything can be connected to the Internet, at anytime, anywhere. This means a plethora of objects (e.g. smart cameras, wearables, environmental sensors, home appliances, and vehicles) are 'connected' and generating massive amounts of data. The collection, integration, processing and analytics of these data enable the realisation of smart cities, infrastructures and services for enhancing the quality of life of humans. Nowadays, existing IoT architectures are highly centralised and heavily rely on transferring data processing, analytics, and decision-making processes to cloud solutions. This approach of managing and processing data at the cloud may lead to inefficiencies in terms of latency, network traffic management, computational processing, and power consumption. Furthermore, in many applications, such as health monitoring and emergency response services, which require low latency, delay caused by transferring data to the cloud and then back to the application can seriously impact their performances. The idea of allowing data processing closer to where data is generated, with techniques such as data fusion, trending of data, and some decision making, can help reduce the amount of data sent to the cloud, reducing network traffic, bandwidth and energy consumption. Also, a more agile response, closer to real-time, will be achieved, which is necessary in applications such as smart health, security and
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.
Issues and Research Paths in Fog Computing
International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2022
Cloud computing is a framework that provides data storage and data processing to edge network users. Until recently, cloud has been a great solution to access our data and process them any time and everywhere. But the price decrease of connected devices with internet network increases the end users' number in the edge network. Consequently, the data coming from edge network will be concentrated around the cloud. This causes congestion and significant response latency of data. Fog computing is installed as a solution for the congestion problem; it is an extension of cloud placed closer to each area of end users. This solution provides low response latency for devices that request data from cloud. It also provides processing and storage features to IoT/sensors witch do not adopt them. In this work, we present Fog computing by defining the limits of cloud computing which led to creating the Fog. Afterwards, we set the Fog computing architecture by underscoring its difference from the cloud. We also specify some issues to improve paths of this new technology. Finally, we present some related works.
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.
The NIST Definition of Fog Computing
2017
111 Managing the data generated by Internet of Things (IoT) sensors is one of the biggest challenges 112 faced when deploying an IoT system. Traditional cloud-based IoT systems are challenged by the 113 large scale, heterogeneity, and high latency witnessed in some cloud ecosystems. One solution is 114 to decentralize applications, management, and data analytics into the network itself using a 115 distributed and federated compute model. This approach has become known as fog 116 computing. This document presents a formal definition of fog and mist computing and how they 117 relate to cloud-based computing models for IoT. This document further characterizes important 118 properties and aspects of fog computing, including service models, deployment strategies, and 119 provides a baseline of what fog computing is, and how it may be used. 120 121
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.
Fog Computing and the Internet of Things: A Review
With the rapid growth of Internet of Things (IoT) applications, the classic centralized cloud computing paradigm faces several challenges such as high latency, low capacity and network failure. To address these challenges, fog computing brings the cloud closer to IoT devices. The fog provides IoT data processing and storage locally at IoT devices instead of sending them to the cloud. In contrast to the cloud, the fog provides services with faster response and greater quality. Therefore, fog computing may be considered the best choice to enable the IoT to provide efficient and secure services for many IoT users. This paper presents the state-of-the-art of fog computing and its integration with the IoT by highlighting the benefits and implementation challenges. This review will also focus on the architecture of the fog and emerging IoT applications that will be improved by using the fog model. Finally, open issues and future research directions regarding fog computing and the IoT are discussed.