Assessment of the Suitability of Fog Computing in the Context of Internet of Things - 2018


This work performs a rigorous, comparative analysis of the fog computing paradigm and the conventional Cloud Computing paradigm in the context of the Internet of Things (IoT), by mathematically formulating the parameters and characteristics of fog computing-one in all the first tries of its kind. With the rapid increase in the amount of Internet-connected devices, the increased demand of real-time, low-latency services is proving to be challenging for the traditional Cloud Computing framework. Conjointly, our irreplaceable dependency on Cloud Computing demands the cloud information centers (DCs) forever to be up and running which exhausts huge amount of power and yield heaps of carbon dioxide (CO2) gas. During this work, we assess the applicability of the newly proposed fog computing paradigm to serve the strain of the latency-sensitive applications within the context of IoT. We model the fog computing paradigm by mathematically characterizing the fog computing network in terms of power consumption, service latency, CO2 emission, and value, and evaluating its performance for an environment with high variety of Internet-connected devices demanding real-time service. A case study is performed with traffic generated from the one hundred highest populated cities being served by eight geographically distributed DCs. Results show that as the quantity of applications demanding real-time service increases, the fog computing paradigm outperforms ancient Cloud Computing. For an atmosphere with 50 p.c applications requesting for instantaneous, real-time services, the overall service latency for fog computing is noted to decrease by fifty.09 percent. However, it's mentionworthy that for an atmosphere with less share of applications demanding for low-latency services, fog computing is observed to be an overhead compared to the ancient Cloud Computing. Therefore, the work shows that within the context of IoT, with high variety of latency-sensitive applications fog computing outperforms Cloud Computing.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Systematic Clinical Evaluation of a Deep Learning Method for Medical Image Segmentation Radiosurgery Application ABSTRACT: We conduct an in-depth analysis of a Deep Learning model by using it to segment three-dimensional
PROJECT TITLE : Attention-Guided Discriminative Region Localization and Label Distribution Learning for Bone Age Assessment ABSTRACT: Bone age assessment, also known as BAA, is an extremely useful tool in the clinical setting
PROJECT TITLE : Corrupted Reference Image Quality Assessment of Denoised Images ABSTRACT: As a new foundation for understanding picture quality and denoising, we present corrupted reference image quality assessment (CRIQA). Denoised
PROJECT TITLE : A Hybrid Framework for Short-Term Risk Assessment of Wind-Integrated Composite Power Systems ABSTRACT: An analytical and simulation method is used in this paper to create a novel paradigm for evaluating wind-integrated
PROJECT TITLE :Exact Assessment of the Delay-Rate Tradeoff in Ergodic Interference Alignment - 2018ABSTRACT:So as to increase the network capability and fulfill the quality of Service needs in multi-user wireless networks, interference

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry