DECA: A Dynamic Energy Cost and Carbon Emission-Efficient Application Placement Method for Edge Clouds

Ahvar, Ehsan; Ahvar, Shohreh; Mann, Zoltán Ádám; Crespi, Noël; Glitho, Roch; García-Alfaro, Joaquín

doi:10.1109/access.2021.3075973

Cited by 25 publications

(12 citation statements)

References 46 publications

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“…In FC paradigms, the energy consumption of distributed heterogeneous resources, as well as the price and carbon emission rate of their energy source, differ which affects carbon emission amount [ 65 ]. There are some efforts from the standardization bodies, for example, the 3rd Generation Partnership Project (3GPP) and the Institute of Electronic and Electrical Engineers (IEEEs) standardization bodies in Energy Saving (ES) standardization definition in Mobile and Wireless communication systems [ 66 ].…”

Section: Open Issues and Challengesmentioning

confidence: 99%

Simulation Tools for Fog Computing: A Comparative Analysis

Fahimullah

Guillaume

Ahvar

et al. 2023

Sensors

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Fog Computing (FC) was introduced to offer resources closer to the users. Researchers propose different solutions to make FC mature and use simulators for evaluating their solutions at early stages. In this paper, we compare different FC simulators based on their technical and non-technical characteristics. In addition, a practical comparison is conducted to compare the three main FC simulators based on their performance such as execution time, CPU, and memory usage for running different applications. The analysis can be helpful for researchers to select the appropriate simulator and platform to evaluate their solutions on different use cases. Furthermore, open issues and challenges for FC simulators are discussed that require attention and need to be addressed in the future.

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Section: Open Issues and Challengesmentioning

confidence: 99%

Simulation Tools for Fog Computing: A Comparative Analysis

Fahimullah

Guillaume

Ahvar

et al. 2023

Sensors

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“…Usually, cloud users requested tasks/applications, which are placed into geo-distributed clouds [23], and these clouds have different networking energy consumption and cost based on the users' locations. However, the large-scale adoption of cloud services mainly relies on minimizing the energy consumption and carbon emissions of their data centers [24]. Thus, optimizing the placement of applications over the cloud can help to minimize energy consumption, carbon emissions, and energy costs of the data centers.…”

Section: An Eco-friendly Approach For Saudi Cloud Data Centers 21 Clo...mentioning

confidence: 99%

“…An energy source's carbon emissions (CO 2 /kWh) describe the amount of carbon released per kilowatt-hour of electricity generated, and the unit used in the experiment (tCO 2 e/kWh) is tons of CO 2 equivalent per kWh. In this work, we have used the data values of carbon emissions stated in [15,24], and these values are also shown in Tab. 5.…”

Section: Co 2 Emissionsmentioning

confidence: 99%

An Eco-Friendly Approach for Reducing Carbon Emissions in Cloud Data Centers

Aldossary¹,

Alharbi²

2022

Computers, Materials &Amp; Continua

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Based on the Saudi Green initiative, which aims to improve the Kingdom's environmental status and reduce the carbon emission of more than 278 million tons by 2030 along with a promising plan to achieve netzero carbon by 2060, NEOM city has been proposed to be the "Saudi hub" for green energy, since NEOM is estimated to generate up to 120 Gigawatts (GW) of renewable energy by 2030. Nevertheless, the Information and Communication Technology (ICT) sector is considered a key contributor to global energy consumption and carbon emissions. The data centers are estimated to consume about 13% of the overall global electricity demand by 2030. Thus, reducing the total carbon emissions of the ICT sector plays a vital factor in achieving the Saudi plan to minimize global carbon emissions. Therefore, this paper aims to propose an eco-friendly approach using a Mixed-Integer Linear Programming (MILP) model to reduce the carbon emissions associated with ICT infrastructure in Saudi Arabia. This approach considers the Saudi National Fiber Network (SNFN) as the backbone of Saudi Internet infrastructure. First, we compare two different scenarios of data center locations. The first scenario considers a traditional cloud data center located in Jeddah and Riyadh, whereas the second scenario considers NEOM as a potential cloud data center new location to take advantage of its green energy infrastructure. Then, we calculate the energy consumption and carbon emissions of cloud data centers and their associated energy costs. After that, we optimize the energy efficiency of different cloud data centers' locations (in the SNFN) to reduce the associated carbon emissions and energy costs. Simulation results show that the proposed approach can save up to 94% of the carbon emissions and 62% of the energy cost compared to the current cloud physical topology. These savings are achieved due to the shifting of cloud data centers from cities that have conventional energy sources to a city that has rich in renewable energy sources. Finally, we design a heuristic algorithm to verify the proposed approach, and it gives equivalent results to the MILP model.

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“…The algorithm equals the compromise between system costs and QoS. Ahvar et al [14] present a dynamic energy and carbon emission-efficient application placement method for cloud servers. This method solves the problems of first placing applications on cloud servers and optimizes placement by migration.…”

Section: Related Workmentioning

confidence: 99%

Reliability modelling and optimization for microservice‐based cloud application using multi‐agent system

Liu

Fan

et al. 2022

IET Communications

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In the process of the continuous development of the Internet of Things, cloud computing has been applied in many fields, how to guarantee the quality of service, such as low latency, high bandwidth, high reliability etc., has become a challenging problem. This paper proposes a method to model and optimize reliability for microservice‐based cloud applications using multi‐agent system (MAS), thus maximizing the reliability of cloud computing and dynamically scheduling microservices to minimize the delay within the budget. Firstly, a dynamic microservice scheduling scheme is proposed to provide efficient computing services by using MAS. A hierarchical cloud computing model is formed by predicated Petri net (PrT net) and the properties of constructed model are analysed. Secondly, agents have been utilized to describe the essential characteristics of microservice scheduling process in the cloud applications. The partial critical path (PCP) aims to maximize the reliability of cloud applications under the limitation of budget and meet the user‐defined deadline. Finally, the proposed PCPRO algorithm has been applied to cloud environment, which is suitable for different scientific workflows in the cloud computing environment. The effectiveness of this method is verified by simulation, the experiment results show the effectiveness of the proposed method.

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DECA: A Dynamic Energy Cost and Carbon Emission-Efficient Application Placement Method for Edge Clouds

Cited by 25 publications

References 46 publications

Simulation Tools for Fog Computing: A Comparative Analysis

Simulation Tools for Fog Computing: A Comparative Analysis

An Eco-Friendly Approach for Reducing Carbon Emissions in Cloud Data Centers

Reliability modelling and optimization for microservice‐based cloud application using multi‐agent system

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