Envisioning Internet of Things using Fog Computing
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 1
Abstract
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.
Authors and Affiliations
Urooj Yousuf Khan, Tariq Rahim Soomro
Keywords
Related Articles
- EP ID EP261913
- DOI 10.14569/IJACSA.2018.090161
- Views 82
- Downloads 0
Analysis of Medical Domain Using CMARM: Confabulation Mapreduce Association Rule Mining Algorithm for Frequent and Rare Itemsets
In Human Life span, disease is a major cause of illness and death in the modern society. There are various factors that are responsible for diseases like work environment, living and working conditions, agriculture and f...
A Fresnelet-Based Encryption of Medical Images using Arnold Transform
Medical images are commonly stored in digital media and transmitted via Internet for certain uses. If a medical information image alters, this can lead to a wrong diagnosis which may create a serious health problem. More...
Analysis of Spatially Modelled High Temperature Polymer Electrolyte Membrane Fuel Cell under Dynamic Load Conditions
This paper presents an interesting approach to observe the effects of the load variations on the performance of high temperature polymer electrolyte membrane fuel cell system, such as: hydrogen and air flow rate, output...
Automated Periodontal Diseases Classification System
This paper presents an efficient and innovative system for automated classification of periodontal diseases, The strength of our technique lies in the fact that it incorporates knowledge from the patients' clinical data,...
Segmentation using Codebook Index Statistics for Vector Quantized Images
In this paper, the segmentation using codebook index statistics (SUCIS) method is proposed for vector-quantized images. Three different codebooks are constructed according to the statistical characteristics (mean, varian...