Pour une meilleure efficacité énergétique dans un système Smart Grid - Cloud

This thesis considers the energy efficiency of information and communication infrastructures in a smart grid - cloud system. It especially deals with communication networks and cloud data centers due to their high energy consumption, which confers them an important role in the network. The contributions of this thesis are implemented on the same framework integrating the smart grid, microgrid, cloud, data centers and users. Indeed, we have studied the interaction between the cloud data centers and the smart grid provider and we have proposed energy efficient power allocation solutions and an energy cost minimization scheme using two architectures: a smart grid-cloud architecture and a microgrid-cloud architecture. In addition, we paid close attention to execute user requests while ensuring a good quality of service in a fog-cloud architecture. In comparison with state-of-the-art works, the results of our contributions have shown that they respond to the identified challenges, particularly in terms of reducing carbon emissions and energy costs of cloud data centers.Dans cette thèse, nous étudions l’efficacité énergétique des infrastructures informatiques dans un système smart grid – cloud. Nous nous intéressons plus particulièrement aux réseaux de communication et aux data centers du cloud. Nous nous focalisons sur ces derniers à cause de leur grande consommation d’énergie et du rôle vital qu’ils jouent dans un monde connecté en pleine expansion, les positionnant, ainsi, comme des éléments importants dans un système smart grid - cloud. De ce fait, les travaux de cette thèse s’inscrivent dans le cadre d’un seul framework intégrant le smart grid, le microgrid, le cloud, les data centers et les utilisateurs. Nous avons, en effet, étudié l’interaction entre les data centers du cloud et le fournisseur d’énergie du smart grid et nous avons proposé des solutions d’allocation d’énergie et de minimisation du coût d’énergie en utilisant deux architectures : (1) une architecture smart grid-cloud et (2) une architecture microgrid-cloud. Par ailleurs, nous avons porté une attention particulière à l’exécution des requêtes des utilisateurs tout en leur garantissant un niveau de qualité de service satisfaisant dans une architecture fog -cloud. En comparaison avec les travaux de l’état de l’art, les résultats de nos contributions ont montré qu’ils répondent aux enjeux identifiés, notamment en réduisant les émissions de gaz à effet de serre et le coût d’énergie des data centers

For better energy efficiency in a Smart Grid – Cloud system

Dans cette thèse, nous étudions l’efficacité énergétique des infrastructures informatiques dans un système smart grid – cloud. Nous nous intéressons plus particulièrement aux réseaux de communication et aux data centers du cloud. Nous nous focalisons sur ces derniers à cause de leur grande consommation d’énergie et du rôle vital qu’ils jouent dans un monde connecté en pleine expansion, les positionnant, ainsi, comme des éléments importants dans un système smart grid - cloud. De ce fait, les travaux de cette thèse s’inscrivent dans le cadre d’un seul framework intégrant le smart grid, le microgrid, le cloud, les data centers et les utilisateurs. Nous avons, en effet, étudié l’interaction entre les data centers du cloud et le fournisseur d’énergie du smart grid et nous avons proposé des solutions d’allocation d’énergie et de minimisation du coût d’énergie en utilisant deux architectures : (1) une architecture smart grid-cloud et (2) une architecture microgrid-cloud. Par ailleurs, nous avons porté une attention particulière à l’exécution des requêtes des utilisateurs tout en leur garantissant un niveau de qualité de service satisfaisant dans une architecture fog -cloud. En comparaison avec les travaux de l’état de l’art, les résultats de nos contributions ont montré qu’ils répondent aux enjeux identifiés, notamment en réduisant les émissions de gaz à effet de serre et le coût d’énergie des data centers.This thesis considers the energy efficiency of information and communication infrastructures in a smart grid - cloud system. It especially deals with communication networks and cloud data centers due to their high energy consumption, which confers them an important role in the network. The contributions of this thesis are implemented on the same framework integrating the smart grid, microgrid, cloud, data centers and users. Indeed, we have studied the interaction between the cloud data centers and the smart grid provider and we have proposed energy efficient power allocation solutions and an energy cost minimization scheme using two architectures: a smart grid-cloud architecture and a microgrid-cloud architecture. In addition, we paid close attention to execute user requests while ensuring a good quality of service in a fog-cloud architecture. In comparison with state-of-the-art works, the results of our contributions have shown that they respond to the identified challenges, particularly in terms of reducing carbon emissions and energy costs of cloud data centers

Pour une meilleure efficacité énergétique dans un système Smart Grid - Cloud

This thesis considers the energy efficiency of information and communication infrastructures in a smart grid - cloud system. It especially deals with communication networks and cloud data centers due to their high energy consumption, which confers them an important role in the network. The contributions of this thesis are implemented on the same framework integrating the smart grid, microgrid, cloud, data centers and users. Indeed, we have studied the interaction between the cloud data centers and the smart grid provider and we have proposed energy efficient power allocation solutions and an energy cost minimization scheme using two architectures: a smart grid-cloud architecture and a microgrid-cloud architecture. In addition, we paid close attention to execute user requests while ensuring a good quality of service in a fog-cloud architecture. In comparison with state-of-the-art works, the results of our contributions have shown that they respond to the identified challenges, particularly in terms of reducing carbon emissions and energy costs of cloud data centers.Dans cette thèse, nous étudions l’efficacité énergétique des infrastructures informatiques dans un système smart grid – cloud. Nous nous intéressons plus particulièrement aux réseaux de communication et aux data centers du cloud. Nous nous focalisons sur ces derniers à cause de leur grande consommation d’énergie et du rôle vital qu’ils jouent dans un monde connecté en pleine expansion, les positionnant, ainsi, comme des éléments importants dans un système smart grid - cloud. De ce fait, les travaux de cette thèse s’inscrivent dans le cadre d’un seul framework intégrant le smart grid, le microgrid, le cloud, les data centers et les utilisateurs. Nous avons, en effet, étudié l’interaction entre les data centers du cloud et le fournisseur d’énergie du smart grid et nous avons proposé des solutions d’allocation d’énergie et de minimisation du coût d’énergie en utilisant deux architectures : (1) une architecture smart grid-cloud et (2) une architecture microgrid-cloud. Par ailleurs, nous avons porté une attention particulière à l’exécution des requêtes des utilisateurs tout en leur garantissant un niveau de qualité de service satisfaisant dans une architecture fog -cloud. En comparaison avec les travaux de l’état de l’art, les résultats de nos contributions ont montré qu’ils répondent aux enjeux identifiés, notamment en réduisant les émissions de gaz à effet de serre et le coût d’énergie des data centers

Power Allocation and Energy Cost Minimization in Cloud Data Centers Microgrids: A Two-Stage Optimization Approach

International audienceData centers are becoming an important asset in today's connected and intelligent world. Indeed, with the emergence of $5G$ networks, the growth of Internet of Things (IoT) and cloud computing, the data centers are increasingly becoming an essential component in delivering our daily services. On the other hand, cloud data centers, are outfitted with power-hungry servers and electrical installations that require enormous quantities of energy. In addition, operating cloud data centers in microgrids can be more reliable and sustainable than having them managed directly by the smart grid operator. However, microgrids have to deal with the high energy cost that their data centers may incur. In this context, managing the power allocated to the data centers and minimizing microgrids energy cost is a challenging problem. In this paper, we model a two-stage optimization approach in a microgrid-cloud architecture. In the first stage, we consider that the cloud data centers are run by multiple providers and try to get as much power as possible from the microgrid, to store this energy and to be able to execute the maximum of users applications. Such a power behavior requires an optimal power assignment from the microgrid to mitigate the risk of blackouts and power outages. Thus, the data center's huge power demand was modeled as a non-cooperative game. The microgrid controller calculates the optimal power that will be assigned to each data center according to its Power Usage Effectiveness (PUE), number of real-time applications and its network bandwidth usage. In the second stage, the microgrids try to minimize their energy cost by optimally purchasing power from the main grid and the other migrogrids, and by selling back their stored energy. We compare our approach with three existing power minimization approaches: (i) our previously presented scheme called 'Basic Game Scheme' (BGS), (ii) traditional and (iii) price-based approaches. Simulations results show that our two stage optimization approach is up to 25% more effective in terms of energy cost. In addition, our scheme promotes MGs green energy usage which significantly reduces power load rate and CO2 emission with a percentage up to 52% comparing to 'BGS' and price-based scheme

Ranking Fog nodes for Tasks Scheduling in Fog-Cloud Environments: A Fuzzy Logic Approach

International audienceFog computing has becoming an attractive solution to face the low responsiveness existing in cloud-based networks. With the rapid emerging of Internet of Things (IoT), more and more terminal nodes are offloading their tasks to nearby fog nodes, located at the network edge, in order to reduce the processing delay. However, this tasks offloading requires an efficient scheduling mechanism that considers both user preferences and fog-cloud requirements. Existing research works for task scheduling in fog-cloud computing networks have mainly focused on reducing task delay and the overall energy consumption, without considering user preferences regarding the fog nodes' constraints. In this work, we present a ranking based task scheduling method that aggregates both user preferences and fog nodes features using linguistic and fuzzy quantified proposition to rank fog nodes from the most to the least satisfactory one. Moreover, we used two parameters called least satisfactory proportion (lsp) and greatest satisfactory proportion (gsp) in order to distinguish the similarities. Experimental results show that our approach satisfies the user preferences, and provides a compromising solution between the average user satisfaction, execution delay and energy consumption

A renewable energy-aware power allocation for cloud data centers: A game theory approach

International audienceWith the rapid emerging of Internet of Things (IoT) devices and the proliferation of cloud-based applications, the cloud computing industry is becoming a vital element for ensuring our daily services. However, cloud computing uses large scale data centers equipped with energy-hungry servers and huge power facilities that massively consume power. This presents a real challenge which can negatively influence the power grid, while exposing the environment to global warming issues. Therefore, minimizing cloud data center power consumption is a challenging problem and has to be addressed. In this paper, we look at renewable energy in the context of a smart grid–cloud architecture and investigate the issue of grid power dispatching to cloud data centers. Since cloud data centers have a non-cooperative nature regarding power demand from the power stations, we model our power allocation problem as a non-cooperative game. Afterwards, we prove the existence and the uniqueness of Nash equilibrium. Moreover, we formulate the payoff function of our game as a non-linear optimization problem before resolving it using Lagrange multipliers and Karush–Kuhn–Tucker (KKT) conditions. Thus, we determine the assigned optimal quantity to each data center based on three main criteria : renewable energy usage, number of critical running applications and workload charge. Extensive simulations are performed by comparing our scheme with an existing work. Results show that our scheme outperforms the comparing approach with a percentage of 31.2% in terms of power load rate and significantly reduces emissions of carbon dioxide

A Game Based Power Allocation in Cloud Computing Data Centers

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A Game Based Power Allocation in Cloud Computing Data Centers

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Power Dispatching in Cloud Data Centers Using Smart Microgrids: A Game Theory Approach

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