IRJET- Connecting Fog and Cloud Computing (original) (raw)
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A Study of Moving from Cloud Computing to Fog Computing
Qubahan Academic Journal, 2021
The exponential growth of the Internet of Things (IoT) technology poses various challenges to the classic centralized cloud computing paradigm, including high latency, limited capacity, and network failure. Cloud computing and Fog computing carry the cloud closer to IoT computers in order to overcome these problems. Cloud and Fog provide IoT processing and storage of IoT items locally instead of sending them to the cloud. Cloud and Fog provide quicker reactions and better efficiency in conjunction with the cloud. Cloud and fog computing should also be viewed as the safest approach to ensure that IoT delivers reliable and stable resources to multiple IoT customers. This article discusses the latest in cloud and Fog computing and their convergence with IoT by stressing deployment's advantages and complexities. It also concentrates on cloud and Fog design and new IoT technologies, enhanced by utilizing the cloud and Fog model. Finally, transparent topics are addressed, along with potential testing recommendations for cloud storage and Fog computing, and IoT.
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: 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.
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.
A Paradigm Shift from Cloud to Fog Computing
The computing scenario is shifting from cloud computing towards edge networking which is known as Fog computing. It is now becoming an important facilitator in upcoming internet of things applications. With the rapid increase in the number of internet connected devices, the increased demand of real-time, low-latency services is proving to be a challenge for the traditional cloud computing framework. Fog computing is observed to be an aerial compared to the traditional cloud. It is hierarchical distributed architecture. This computing ensures the low and predictable latency in the latency-sensitive of Internet of Things (IoT) applications such as the healthcare services which is primary objective of this computing. This paper focuses on architecture, policy manager involved in this novel computing technology and with its usage and applicabilty.
A Comparative Study of Cloud and Fog Computing
Journal of emerging technologies and innovative research, 2019
In this contemporary era, although with the increasing usage of cloud computing, there are still some challenges which are unresolved such as real time latency, lack of mobility support, low capacity, network failure etc. Fog computing can deal with these problems by providing expandable resources and services to the end users, at the edge of network, while cloud computing are more about providing resources distributed in the core network. Generally, Fog computing resides closer to the devices that extend the Cloud-based computing, storage and networking facilities. These devices, called fog nodes, can be deployed anywhere with a network connection: on a factory floor, on top of a power pole, alongside a road or train track, in any automobile vehicle. Any device with computing, storage, and network connectivity can be a fog node. In this comparative study, we elaborate the comparison among cloud and fog on the basis of some parameters like security and privacy issues, data processin...
Fog Computing: An Efficient Platform for the Cloud-resource Management
JETIR, 2019
Datacenters in cloud paradigm are storing enormous data size, and have an impact on both the energy consumptions as well service costs. Although centralized cloud computing is still more convenient, feasible platform for most of real-time applications and services but not the best. As in centralized distributed environment, resource provision and optimal usage of the configurable resources is somewhat neglected and quality of services are ignored, oversized data communication with low bandwidth network capability leads to the congestion in network data transportation, high latencies, delays and network jitters. Lack of proper resource provisioning leads to the unsophisticated energy management which burdens and laden high energy costs on the end-users. These heavy sized cloud macro data centers have negative impact on the environment as these exchange excessive heat while processing. Recent times marvelous research is being taking place that will provide the new horizons to explore and exploit the new horizons of the distributed technologies. The latest one in the town is the Cisco's fog-edge computing and is being considered as the next step in the distributed computing paradigm. Here in this paper, we the authors, consider Fog computing as a convenient and an energy efficient computational platform for resource provisioning, and its impact on optimal costs for the computing resources like services and applications.. Keywords-Centralized Cloud, Real-Time applications, Resource Provisioning 1. Introduction Distributed Cloud computing is the core platform for various evolving technologies likes IoT, Mist, Edge and Fog computing as it sophisticatedly changing ways, the various resources, computational processing, network bandwidth and unlimited storage is being offered with minimal interference and less costs on demand basis [1]. Fog computing main purpose is to take the computational processing and intelligence at the edge of network rather than at macro-core cloud network. Fog is mini-cloud with advantageous features reducing the flaws and limitations i.e. bottlenecks, high latencies, geographical and widely dispersed aerial locations of cloud computing. Fog computing is convenient platform for IoT enabled scenarios i.e. smart (grids, cities, connected vehicles, traffic lighting systems), geographically distributed, real-time sensitive latency bounded applications and act as an intermediate layer between cloud and edge computing, serves various benefits and is now considered to be the future alternative of it[2]. The storage and computational power is being severed at the nano data centers (micro servers) in fog-edge network, rather than sending it to the centralized core cloud network lowering the further latency and time delays, Since the data transformation from the end user devices to the macro-core data centers is a cumbersome process and is energy inefficient, the more is the hops count, the more delay jitters are occurring and cause the highest latencies and time delays. In this paper the more attention is on applications running in fog-edge network and are energy efficient compared to same applications and services running over entirely core-cloud centralized network [3]. The efficient energy management model is of importance to monitor and control the energy consumptions. Proliferation in technology paved more opportunities and possibilities to minimize the energy constraints by enabling the portable less power consuming and high performing RFID tagged end devices enable to make energy efficient systems [4]. These systems make possible cost feasibility and portability, reduction in physical shape and size (Sensors, Actuators, Network-adapters, Switches, Routers, and Fog-Smart Gateways) [5]. In this article our motto is to consider and introduce Fog platform as a novel platform for some of cloud constraints like flexibility, interactivity, scalability, and interoperability among various fog-edge devices, lowering the energy management costs. In this paper, we the authors present the computing resource management with fog computing and the remaining portion of the paper is being categorized in sections. Section I is an introductory part, Section II present the related work, while as Section III present the research challenges, Section IV describe briefly on the problem statement, Section V, fog-based cloud resource management and finally in Section VI, we conclude the paper.
The Rise of Fog Computing in the Digital Era, 2019
Pushing computing, control, data storage, and processing into the cloud has been a key trend in the past decade. However, the cloud alone encounters growing limitations, such as reduced latency, high mobility, high scalability, and real-time execution in order to meet the upcoming computing and intelligent networking demands. A new paradigm called fog computing has emerged to overcome these limits. Fog extends cloud computing and services to the edge of the network. It provides data, computing, storage, and application services to end-users that can be hosted at the network edge. It reduces service latency, and improves QoS/QoE, that results in superior user experience. This chapter is about introduction and overview of fog computing, comparison between fog computing and cloud computing, fog computing and mobile edge computing, possible fog computing architecture, applications of fog computing, and possible research directions.
IRJET- Studying Cloud Vs Fog Computing and its Application
IRJET, 2021
The exponential broadening of the Internet of Things (IoT) constitutes many tough conditions for the conventional paradigm of centralized cloud computing, such as immoderate latency, restricted capacity, and network outages. Cloud computing and Fog computing convey the cloud nearer to IoT computers to defeat these issues. They come up with providing local IoT processing and storage of IoT elements in place of sending them to the cloud. Cloud and Fog bring forth feedback at quicker speeds and better overall performance as compared to the cloud. More secure path of action to make certain that the IoT offers sturdy and dependable assets for multiple IoT customer. The paper presents cloud and fog layout in addition to new IoT technologies, maximum advantageously via the usage of the cloud and fog model and also applications of fog computing.
IRJET- Cloud Computing and Fog Computing: A Survey
IRJET, 2020
Cloud computing is the most vastly developing and expanding segment of the internet. The increased demand gives rise to new concerns over data security, control, privacy and availability. The development in cloud infrastructure leads to increased number of dimensions such as multi latency, elasticity that complicate the security problem. Also, the demand for high efficiency leads to development of new cloud architectures. The main concerns of any cloud user now are reduce latency, improved security and ease of use leading to ultimately having an improved QoS. Increased use in Internet of Things has also increased the demand for more available cloud computation requirements. In contrast, Fog computing is much more localized and is almost always under the complete control of the user and is more immune from outsider attacks. Fog computing can be seen as the scaled down version of a cloud computing system as it has nearly all the properties of a traditional cloud computing system, only in a slightly scaled down form. This includes but not limited to the performance capabilities, storage capacity and other characteristics.