To solve the problem of energy efficiency of modern enterprise it is necessary to reduce energy consumption.One of the possible ways is proposed in this research.A multi-level hierarchical system for energy efficiency...To solve the problem of energy efficiency of modern enterprise it is necessary to reduce energy consumption.One of the possible ways is proposed in this research.A multi-level hierarchical system for energy efficiency management of the enterprise is designed,it is based on the modular principle providing rapid modernization.The novelty of the work is the development of new and improvement of the existing methods and models,in particular:1)models for dynamic analysis of IT tools for data acquisition and processing(DAAP)in multilevel energy management systems,which are based on Petri nets;2)method of synthesis of DAAP tools in energy efficiency management information systems(EEMIS)of the enterprise which provides a reduction in hardware and time costs from 10%to 40%;3)method of conflict-free data exchange determining the minimum memory speed for the synthesis of realtime exchanges,it reduces the cost and energy consumption;4)method of calculating the signal of postsynaptic excitation of neural elements decreases the processing time of technological data two or more times.The proposed methods,models and tools have been tested while implementing the EEMIS of the intelligent mini-greenhouse,as a result,energy efficiency has increased by 12%-25%(depending on season and peculiarities of growing plants).展开更多
As energy efficiency is one of the key essentials towards sustainability, the development of an energy-resource efficient manufacturing system is among the great challenges facing the current industry. Meanwhile, the ...As energy efficiency is one of the key essentials towards sustainability, the development of an energy-resource efficient manufacturing system is among the great challenges facing the current industry. Meanwhile, the availability of advanced technological innovation has created more complex manufacturing systems that involve a large variety of processes and machines serving different functions. To extend the limited knowledge on energy-efficient scheduling, the research presented in this paper attempts to model the production schedule at an operation process by considering the balance of energy consumption reduction in production, production work flow （productivity） and quality. An innovative systematic approach to manufacturing energy-resource efficiency is proposed with the virtual simulation as a predictive modelling enabler, which provides real-time manufacturing monitoring, virtual displays and decision-makings and consequentially an analytical and multidimensional correlation analysis on interdependent relationships among energy consumption, work flow and quality errors. The regression analysis results demonstrate positive relationships between the work flow and quality errors and the work flow and energy consumption. When production scheduling is controlled through optimization of work flow, quality errors and overall energy consumption, the energy-resource efficiency can be achieved in the production. Together, this proposed multidimensional modelling and analysis approach provides optimal conditions for the production scheduling at the manufacturing system by taking account of production quality, energy consumption and resource efficiency, which can lead to the key competitive advantages and sustainability of the system operations in the industry.展开更多
This work surveys and illustrates multiple open challenges in the field of industrial Internet of Things(IoT)-based big data management and analysis in cloud environments.Challenges arising from the fields of machine ...This work surveys and illustrates multiple open challenges in the field of industrial Internet of Things(IoT)-based big data management and analysis in cloud environments.Challenges arising from the fields of machine learning in cloud infrastructures,artificial intelligence techniques for big data analytics in cloud environments,and federated learning cloud systems are elucidated.Additionally,reinforcement learning,which is a novel technique that allows large cloud-based data centers,to allocate more energy-efficient resources is examined.Moreover,we propose an architecture that attempts to combine the features offered by several cloud providers to achieve an energy-efficient industrial IoT-based big data management framework(EEIBDM)established outside of every user in the cloud.IoT data can be integrated with techniques such as reinforcement and federated learning to achieve a digital twin scenario for the virtual representation of industrial IoT-based big data of machines and room tem-peratures.Furthermore,we propose an algorithm for determining the energy consumption of the infrastructure by evaluating the EEIBDM framework.Finally,future directions for the expansion of this research are discussed.展开更多
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 ...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.展开更多
Energy consumption in data centers has grown out of proportion in regard to the state of energy that’s available in the universe. Technology has improved services and its application. The need for eco-friendly energy...Energy consumption in data centers has grown out of proportion in regard to the state of energy that’s available in the universe. Technology has improved services and its application. The need for eco-friendly energy and increase in data centers performance brought about Green Computing into the energy consumption of data centers. Information technology has grown and eaten deep into the society that almost all the sectors if not all are dependent on information technology to move on. The consumption of power has increased greatly. In this research paper the techniques for optimizing energy in data centers for Green Computing would be discussed. This study intends to expose the limitations of existing security solutions for securing data centers by taking into consideration of limitations of existing security frameworks that cannot enhance the security of data centers.展开更多
In a context of growing efforts to develop sustainability strategies, energy-related issues occupy central stage in the built environment. Thus, the energy performance of housings has improved radically over the past ...In a context of growing efforts to develop sustainability strategies, energy-related issues occupy central stage in the built environment. Thus, the energy performance of housings has improved radically over the past decades. Yet other types of buildings, in particular commercial centers, haven’t received the same level of interest. As a result, there is a need for effective and practical measures to decrease their energy consumption, both for heating and electricity. The objective of the paper is to demonstrate that it is possible, through coherent strategies, to integrate energy issues and bioclimatic principles into the design process of commercial centers. It analyzes the exemplary case study of Marin Commercial Center (Switzerland). The interdisciplinary approach, based on integrated design strategies, aimed at increasing the energy efficiency while keeping the cost comparable to the market cost. The main design principles include natural ventilation, nighttime cooling with energy recovery and natural lighting, as well as optimization of mechanical systems. The results of the simulations show that Marin Center attains the best energy performance observed so far among Swiss commercial centers. It also meets the Swiss Minergie standard. The paper thus questions traditional design processes and outlines the need for interdisciplinary evaluation and monitoring approaches tailored for commercial centers. Even though most crucial decisions are taken during the early stages, all phases of the process require systematic optimization strategies, especially operating stages. Recommendations include legal measures, in particular in the fields of ventilation and air-conditioning, education, professional development and technology transfer, and financial incentives for the replacement of energy intensive installations.展开更多
Both performance and energy cost are impor- tant concerns for current data center operators. Traditionally, however, IT and mechanical engineers have separately op- timized the cyber and physical aspects of data cente...Both performance and energy cost are impor- tant concerns for current data center operators. Traditionally, however, IT and mechanical engineers have separately op- timized the cyber and physical aspects of data center operations. This paper considers both of these aspects with the eventual goal of developing performance and power management techniques that operate holistically to control the entire cyber-physical complex of data center installations. Toward this end, we propose a balance of payments model for holis- tic power and performance management. As an example of coordinated cyber-physical system management, the energy- aware cyber-physical system （EaCPS） uses an application controller on the cyber side to guarantee application perfor- mance, and on the physical side, it utilizes electric current- aware capacity management （CACM） to smartly place exe- cutables to reduce the energy consumption of each chassis present in a data center rack. A web application, representa- tive of a multi-tier web site, is used to evaluate the perfor- mance of the controller on the cyber side, the CACM control on the physical side, and the holistic EaCPS methods in a mid-size instrumented data center. Results indicate that coor- dinated EaCPS outperforms separate cyber and physical con- trol modules.展开更多
文摘To solve the problem of energy efficiency of modern enterprise it is necessary to reduce energy consumption.One of the possible ways is proposed in this research.A multi-level hierarchical system for energy efficiency management of the enterprise is designed,it is based on the modular principle providing rapid modernization.The novelty of the work is the development of new and improvement of the existing methods and models,in particular:1)models for dynamic analysis of IT tools for data acquisition and processing(DAAP)in multilevel energy management systems,which are based on Petri nets;2)method of synthesis of DAAP tools in energy efficiency management information systems(EEMIS)of the enterprise which provides a reduction in hardware and time costs from 10%to 40%;3)method of conflict-free data exchange determining the minimum memory speed for the synthesis of realtime exchanges,it reduces the cost and energy consumption;4)method of calculating the signal of postsynaptic excitation of neural elements decreases the processing time of technological data two or more times.The proposed methods,models and tools have been tested while implementing the EEMIS of the intelligent mini-greenhouse,as a result,energy efficiency has increased by 12%-25%(depending on season and peculiarities of growing plants).
基金Supported by the EU 7th Framework ICT Programme under Euro Energest Project(Contract No.288102)
文摘As energy efficiency is one of the key essentials towards sustainability, the development of an energy-resource efficient manufacturing system is among the great challenges facing the current industry. Meanwhile, the availability of advanced technological innovation has created more complex manufacturing systems that involve a large variety of processes and machines serving different functions. To extend the limited knowledge on energy-efficient scheduling, the research presented in this paper attempts to model the production schedule at an operation process by considering the balance of energy consumption reduction in production, production work flow （productivity） and quality. An innovative systematic approach to manufacturing energy-resource efficiency is proposed with the virtual simulation as a predictive modelling enabler, which provides real-time manufacturing monitoring, virtual displays and decision-makings and consequentially an analytical and multidimensional correlation analysis on interdependent relationships among energy consumption, work flow and quality errors. The regression analysis results demonstrate positive relationships between the work flow and quality errors and the work flow and energy consumption. When production scheduling is controlled through optimization of work flow, quality errors and overall energy consumption, the energy-resource efficiency can be achieved in the production. Together, this proposed multidimensional modelling and analysis approach provides optimal conditions for the production scheduling at the manufacturing system by taking account of production quality, energy consumption and resource efficiency, which can lead to the key competitive advantages and sustainability of the system operations in the industry.
文摘This work surveys and illustrates multiple open challenges in the field of industrial Internet of Things(IoT)-based big data management and analysis in cloud environments.Challenges arising from the fields of machine learning in cloud infrastructures,artificial intelligence techniques for big data analytics in cloud environments,and federated learning cloud systems are elucidated.Additionally,reinforcement learning,which is a novel technique that allows large cloud-based data centers,to allocate more energy-efficient resources is examined.Moreover,we propose an architecture that attempts to combine the features offered by several cloud providers to achieve an energy-efficient industrial IoT-based big data management framework(EEIBDM)established outside of every user in the cloud.IoT data can be integrated with techniques such as reinforcement and federated learning to achieve a digital twin scenario for the virtual representation of industrial IoT-based big data of machines and room tem-peratures.Furthermore,we propose an algorithm for determining the energy consumption of the infrastructure by evaluating the EEIBDM framework.Finally,future directions for the expansion of this research are discussed.
文摘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.
文摘Energy consumption in data centers has grown out of proportion in regard to the state of energy that’s available in the universe. Technology has improved services and its application. The need for eco-friendly energy and increase in data centers performance brought about Green Computing into the energy consumption of data centers. Information technology has grown and eaten deep into the society that almost all the sectors if not all are dependent on information technology to move on. The consumption of power has increased greatly. In this research paper the techniques for optimizing energy in data centers for Green Computing would be discussed. This study intends to expose the limitations of existing security solutions for securing data centers by taking into consideration of limitations of existing security frameworks that cannot enhance the security of data centers.
文摘In a context of growing efforts to develop sustainability strategies, energy-related issues occupy central stage in the built environment. Thus, the energy performance of housings has improved radically over the past decades. Yet other types of buildings, in particular commercial centers, haven’t received the same level of interest. As a result, there is a need for effective and practical measures to decrease their energy consumption, both for heating and electricity. The objective of the paper is to demonstrate that it is possible, through coherent strategies, to integrate energy issues and bioclimatic principles into the design process of commercial centers. It analyzes the exemplary case study of Marin Commercial Center (Switzerland). The interdisciplinary approach, based on integrated design strategies, aimed at increasing the energy efficiency while keeping the cost comparable to the market cost. The main design principles include natural ventilation, nighttime cooling with energy recovery and natural lighting, as well as optimization of mechanical systems. The results of the simulations show that Marin Center attains the best energy performance observed so far among Swiss commercial centers. It also meets the Swiss Minergie standard. The paper thus questions traditional design processes and outlines the need for interdisciplinary evaluation and monitoring approaches tailored for commercial centers. Even though most crucial decisions are taken during the early stages, all phases of the process require systematic optimization strategies, especially operating stages. Recommendations include legal measures, in particular in the fields of ventilation and air-conditioning, education, professional development and technology transfer, and financial incentives for the replacement of energy intensive installations.
文摘Both performance and energy cost are impor- tant concerns for current data center operators. Traditionally, however, IT and mechanical engineers have separately op- timized the cyber and physical aspects of data center operations. This paper considers both of these aspects with the eventual goal of developing performance and power management techniques that operate holistically to control the entire cyber-physical complex of data center installations. Toward this end, we propose a balance of payments model for holis- tic power and performance management. As an example of coordinated cyber-physical system management, the energy- aware cyber-physical system （EaCPS） uses an application controller on the cyber side to guarantee application perfor- mance, and on the physical side, it utilizes electric current- aware capacity management （CACM） to smartly place exe- cutables to reduce the energy consumption of each chassis present in a data center rack. A web application, representa- tive of a multi-tier web site, is used to evaluate the perfor- mance of the controller on the cyber side, the CACM control on the physical side, and the holistic EaCPS methods in a mid-size instrumented data center. Results indicate that coor- dinated EaCPS outperforms separate cyber and physical con- trol modules.
