Abstract

In this work, a new orchestration of Consumer to Fog to Cloud (C2F2C) based framework is proposed for efficiently managing the resources in residential buildings. C2F2C is a three layered framework consisting of cloud layer, fog layer and consumer layer. Cloud layer deals with on-demand delivery of the consumer’s demands. Resource management is intelligently done through the fog layer because it reduces the latency and enhances the reliability of cloud. Consumer layer is based on the residential users and their electricity demands from the six regions of the world. These regions are categorized on the bases of the continents. Two control parameters are considered: clusters of buildings and load requests, whereas four performance parameters are considered: Request Per Hour (RPH), Response Time (RT), Processing Time (PT) and cost in terms of Virtual Machines (VMs), Microgrids (MGs) and data transfer. These parameters are analysed by the round robin algorithm, equally spread current execution algorithm and our proposed algorithm shortest job first. Two scenarios are used in the simulations: resource allocation using MGs and resource allocation using MGs and power storage devices for checking the effectiveness of the proposed work. The simulation results of the proposed technique show that it has outperformed the previous techniques in terms of the above-mentioned parameters. There exists a tradeoff in the PT and RT as compared to cost of VM, MG and data transfer.

Highlights

  • In Smart Grig (SG), Demand Side Management (DSM) with the integration of Information and Communication Technologies (ICTs) is considered as its paramount function

  • We have proposed the concept of C2F2C based environment in order to minimize the latency and efficient scheduling of the resources in the residential buildings

  • This study considers the optimal Response Time (RT), cost of data transfer, MG and Virtual Machines (VMs), consumers’ requests time and Processing Time (PT), which is provided by fog computing

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Summary

Introduction

In Smart Grig (SG), Demand Side Management (DSM) with the integration of Information and Communication Technologies (ICTs) is considered as its paramount function. The technical aspect considers the huge size data of the appliances which means the number of appliances used in the smart buildings, their power ratings, their On and Off status, and scheduling horizons. It needs to be processed by considering the specific time constraints for maintaining its computational complexity. The management of computation, storage and on-demand resource availability from grid and electricity scheduling for the consumers is handled by cloud computing. Cloud computing resolves both technical and economical aspects of these (computation, storage and on-demand resource availability) problems It is the enhanced version of the parallel and grid computing. Reliability, security and latency of the consumers’ demands [7,8,9]

Motivation
Contributions
Literature Review
Methodologies Regarding Cloud Based Architecture
Methodologies Regarding Fog Based Architecture
Proposed System
Assumptions
Problem Formulation
Proposed C2F2C Framework
Twenty Five VMs with Single DC
Fifty VMs with Two DCs
The RR Algorithm
The ESCE Algorithm
The SJF Algorithm
Simulation Results
Scenario 1
Scenario 2
Critical Analysis
Full Text
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