Abstract

The computing devices in data centers of cloud and fog remain in continues running cycle to provide services. The long execution state of large number of computing devices consumes a significant amount of power, which emits an equivalent amount of heat in the environment. The performance of the devices is compromised in heating environment. The high powered cooling systems are installed to cool the data centers. Accordingly, data centers demand high electricity for computing devices and cooling systems. Moreover, in Smart Grid (SG) managing energy consumption to reduce the electricity cost for consumers and minimum rely on fossil fuel based power supply (utility) is an interesting domain for researchers. The SG applications are time-sensitive. In this paper, fog based model is proposed for a community to ensure real-time energy management service provision. Three scenarios are implemented to analyze cost efficient energy management for power-users. In first scenario, community’s and fog’s power demand is fulfilled from the utility. In second scenario, community’s Renewable Energy Resources (RES) based Microgrid (MG) is integrated with the utility to meet the demand. In third scenario, the demand is fulfilled by integrating fog’s MG, community’s MG and the utility. In the scenarios, the energy demand of fog is evaluated with proposed mechanism. The required amount of energy to run computing devices against number of requests and amount of power require cooling down the devices are calculated to find energy demand by fog’s data center. The simulations of case studies show that the energy cost to meet the demand of the community and fog’s data center in third scenario is 15.09% and 1.2% more efficient as compared to first and second scenarios, respectively. In this paper, an energy contract is also proposed that ensures the participation of all power generating stakeholders. The results advocate the cost efficiency of proposed contract as compared to third scenario. The integration of RES reduce the energy cost and reduce emission of CO 2 . The simulations for energy management and plots of results are performed in Matlab. The simulation for fog’s resource management, measuring processing, and response time are performed in CloudAnalyst.

Highlights

  • Electricity is categorized as a basic right or basic need for people in the world [1,2]

  • The utility energy cost depends on the cost of the amount of energy produced from fossil fuel based generators (∆C f uel ), cost of energy bought from the community MG (∆cost for community MG (Ccmg) ), and the cost of amount of energy bought from FMG (∆C f mg ), as computed with Equation (19)

  • The requests are allocated to Virtual Machine (VM) by balancing the load on them using intelligent load balancer, e.g., modified honey bee colony optimization

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Summary

Introduction

Electricity is categorized as a basic right or basic need for people in the world [1,2]. The integration of RES based Microgrids (MGs) with existing system fulfills economical and environment friendly power demand. Energy trading strategies are inevitable to integrate RES in existing power system for the fulfillment of economical and environment friendly power demand. Time (RT) [23,24], high computation heats the physical resources, which are cooled by high powered air-conditioning systems, which increase service cost [25], and economical and environmental friendly huge power generation is challenging [26], especially for increasing demand of computing devices and cooling system data center is challenging [27]. The fog equipped with green (renewable) energy for a community provides near real-time response with environment friendly power management services.

Related Work
Limitations
Proposed System Model
Problem Formulation
Contract for Energy Trade
Case Studies
Discussion and Results
Case Study
Summary of Proposed Solution
Limitation
Conclusions
Full Text
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