Fog Computing: A New Era of Cloud Computing

Author(s):  
S. Delfin ◽  
N.P Sivasanker. ◽  
Nishant Raj ◽  
Ashish Anand
2018 ◽  
Vol 7 (2.7) ◽  
pp. 345
Author(s):  
Chandra Sekhar Maganty ◽  
Kothamasu Kiran Kumar

Cloud computing is the transformation, which involves storing large applications where data or information is exchanged among differ-ent platforms for giving good service to clients who belong to different organizations. It assures great use of resources by making data, software and infrastructure available with minimal cost along with security and reliability. Even though cloud computing gives many advantages, it has certain limitations like network congestion, fault tolerance, less bandwidth etc. To come out of this issue a new era computing model is introduced called Fog Computing. This new computing model can transfer fragile data without any delay to other devices in the network. The only difference between both is fog is located more close to the end user or the device and gives response to the client instantly. Moreover, it is beneficial to the real time streaming applications, internet of things which need reliable internet con-nectivity along with high speed. This paper is a review on Fog Computing, differences in edge and fog computing, use cases of fog and the architecture.


Internet of things (IoT) is an emerging concept which aims to connect billions of devices with each other anytime regardless of their location. Sadly, these IoT devices do not have enough computing resources to process huge amount of data. Therefore, Cloud computing is relied on to provide these resources. However, cloud computing based architecture fails in applications that demand very low and predictable latency, therefore the need for fog computing which is a new paradigm that is regarded as an extension of cloud computing to provide services between end users and the cloud user. Unfortunately, Fog-IoT is confronted with various security and privacy risks and prone to several cyberattacks which is a serious challenge. The purpose of this work is to present security and privacy threats towards Fog-IoT platform and discuss the security and privacy requirements in fog computing. We then proceed to propose an Intrusion Detection System (IDS) model using Standard Deep Neural Network's Back Propagation algorithm (BPDNN) to mitigate intrusions that attack Fog-IoT platform. The experimental Dataset for the proposed model is obtained from the Canadian Institute for Cybersecurity 2017 Dataset. Each instance of the attack in the dataset is separated into separate files, which are DoS (Denial of Service), DDoS (Distributed Denial of Service), Web Attack, Brute Force FTP, Brute Force SSH, Heartbleed, Infiltration and Botnet (Bot Network) Attack. The proposed model is trained using a 3-layer BP-DNN


2018 ◽  
Vol 10 (3) ◽  
pp. 61-83 ◽  
Author(s):  
Deepali Chaudhary ◽  
Kriti Bhushan ◽  
B.B. Gupta

This article describes how cloud computing has emerged as a strong competitor against traditional IT platforms by offering low-cost and “pay-as-you-go” computing potential and on-demand provisioning of services. Governments, as well as organizations, have migrated their entire or most of the IT infrastructure to the cloud. With the emergence of IoT devices and big data, the amount of data forwarded to the cloud has increased to a huge extent. Therefore, the paradigm of cloud computing is no longer sufficient. Furthermore, with the growth of demand for IoT solutions in organizations, it has become essential to process data quickly, substantially and on-site. Hence, Fog computing is introduced to overcome these drawbacks of cloud computing by bringing intelligence to the edge of the network using smart devices. One major security issue related to the cloud is the DDoS attack. This article discusses in detail about the DDoS attack, cloud computing, fog computing, how DDoS affect cloud environment and how fog computing can be used in a cloud environment to solve a variety of problems.


2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Yutong Zhou ◽  
Wei Shi ◽  
Fei Song

Mobile Fog Computing (MFC), as a crucial supplement to cloud computing, has its own special traits in many aspects. As smart mobile devices grow and vary in shapes and formats over the years, the need for real-time interactions and an easy-to-use network is imminent. In this paper, we propose a smart collaborative policy for MFC scenarios by considering the target of rural vitalization. The challenges and drawbacks of extending cloud to fog are reviewed at the beginning. Then, the analysis of policy design is presented from the perspectives of feature comparisons, urgent requirements, and possible solutions. The details of policy establishment are introduced with necessary examples. Finally, performance evaluations are provided based on simulation platforms. Validation results related to round trip time and transmission time illustrate the significant improvements of our proposal in certain ways compared to the original candidate, which enables larger deployment in impoverished areas.


2018 ◽  
Vol 6 (4) ◽  
pp. 39-47 ◽  
Author(s):  
Reuben Ng

Cloud computing adoption enables big data applications in governance and policy. Singapore’s adoption of cloud computing is propelled by five key drivers: (1) public demand for and satisfaction with e-government services; (2) focus on whole-of-government policies and practices; (3) restructuring of technology agencies to integrate strategy and implementation; (4) building the Smart Nation Platform; (5) purpose-driven cloud applications especially in healthcare. This commentary also provides recommendations to propel big data applications in public policy and management: (a) technologically, embrace cloud analytics, and explore “fog computing”—an emerging technology that enables on-site data sense-making before transmission to the cloud; (b) promote regulatory sandboxes to experiment with policies that proactively manage novel technologies and business models that may radically change society; (c) on the collaboration front, establish unconventional partnerships to co-innovate on challenges like the skills-gap—an example is the unprecedented partnership led by the Lee Kuan Yew School of Public Policy with the government, private sector and unions.


2020 ◽  
Vol 21 (1) ◽  
pp. 6-12
Author(s):  
Javier Pinzón Castellanos ◽  
Miguel Antonio Cadena Carter

Fog Computing is the distributed computing layer that lies between the user and the cloud. A successful fog architecture reduces delay or latency and increases efficiency. This paper describes the development and implementation of a distributed computing architecture applied to an automation environment that uses Fog Computing as an intermediary with the cloud computing layer. This study used a Raspberry Pi V3 board connected to end control elements such as servomotors and relays, indicators and thermal sensors. All is controlled by an automation framework that receives orders from Siri and executes them through predetermined instructions. The cloud connection benefits from a reduced amount of data transmission, because it only receives relevant information for analysis.


Sign in / Sign up

Export Citation Format

Share Document