1. The document discusses developing an energy-efficient task scheduling approach for cloud data centers using deep reinforcement learning.
2. It aims to minimize computational costs and cooling costs by optimizing task assignment to servers based on factors like temperature, CPU, and memory.
3. The proposed approach uses a greedy algorithm to schedule tasks to servers maintaining the lowest temperature, thus reducing energy consumption and improving data center performance.
A Review on Scheduling in Cloud Computingijujournal
Cloud computing is the requirement based on clients that this computing which provides software,
infrastructure and platform as a service as per pay for use norm. The scheduling main goal is to achieve
the accuracy and correctness on task completion. The scheduling in cloud environment which enables the
various cloud services to help framework implementation. Thus the far reaching way of different type of
scheduling algorithms in cloud computing environment surveyed which includes the workflow scheduling
and grid scheduling. The survey gives an elaborate idea about grid, cloud, workflow scheduling to
minimize the energy cost, efficiency and throughput of the system.
A Review on Scheduling in Cloud Computingijujournal
Cloud computing is the requirement based on clients that this computing which provides software,
infrastructure and platform as a service as per pay for use norm. The scheduling main goal is to achieve
the accuracy and correctness on task completion. The scheduling in cloud environment which enables the
various cloud services to help framework implementation. Thus the far reaching way of different type of
scheduling algorithms in cloud computing environment surveyed which includes the workflow scheduling
and grid scheduling. The survey gives an elaborate idea about grid, cloud, workflow scheduling to
minimize the energy cost, efficiency and throughput of the system.
A Review on Scheduling in Cloud Computingijujournal
Cloud computing is the requirement based on clients that this computing which provides software,
infrastructure and platform as a service as per pay for use norm. The scheduling main goal is to achieve
the accuracy and correctness on task completion. The scheduling in cloud environment which enables the
various cloud services to help framework implementation. Thus the far reaching way of different type of
scheduling algorithms in cloud computing environment surveyed which includes the workflow scheduling
and grid scheduling. The survey gives an elaborate idea about grid, cloud, workflow scheduling to
minimize the energy cost, efficiency and throughput of the system
A Review on Scheduling in Cloud Computingijujournal
Cloud computing is the requirement based on clients that this computing which provides software,
infrastructure and platform as a service as per pay for use norm. The scheduling main goal is to achieve
the accuracy and correctness on task completion. The scheduling in cloud environment which enables the
various cloud services to help framework implementation. Thus the far reaching way of different type of
scheduling algorithms in cloud computing environment surveyed which includes the workflow scheduling
and grid scheduling. The survey gives an elaborate idea about grid, cloud, workflow scheduling to
minimize the energy cost, efficiency and throughput of the system.
A Review on Scheduling in Cloud Computingijujournal
Cloud computing is the requirement based on clients that this computing which provides software,
infrastructure and platform as a service as per pay for use norm. The scheduling main goal is to achieve
the accuracy and correctness on task completion. The scheduling in cloud environment which enables the
various cloud services to help framework implementation. Thus the far reaching way of different type of
scheduling algorithms in cloud computing environment surveyed which includes the workflow scheduling
and grid scheduling. The survey gives an elaborate idea about grid, cloud, workflow scheduling to
minimize the energy cost, efficiency and throughput of the system.
A Review on Scheduling in Cloud Computingijujournal
Cloud computing is the requirement based on clients that this computing which provides software,
infrastructure and platform as a service as per pay for use norm. The scheduling main goal is to achieve
the accuracy and correctness on task completion. The scheduling in cloud environment which enables the
various cloud services to help framework implementation. Thus the far reaching way of different type of
scheduling algorithms in cloud computing environment surveyed which includes the workflow scheduling
and grid scheduling. The survey gives an elaborate idea about grid, cloud, workflow scheduling to
minimize the energy cost, efficiency and throughput of the system.
A Review on Scheduling in Cloud Computingijujournal
Cloud computing is the requirement based on clients that this computing which provides software,
infrastructure and platform as a service as per pay for use norm. The scheduling main goal is to achieve
the accuracy and correctness on task completion. The scheduling in cloud environment which enables the
various cloud services to help framework implementation. Thus the far reaching way of different type of
scheduling algorithms in cloud computing environment surveyed which includes the workflow scheduling
and grid scheduling. The survey gives an elaborate idea about grid, cloud, workflow scheduling to
minimize the energy cost, efficiency and throughput of the system
A Review on Scheduling in Cloud Computingijujournal
Cloud computing is the requirement based on clients that this computing which provides software,
infrastructure and platform as a service as per pay for use norm. The scheduling main goal is to achieve
the accuracy and correctness on task completion. The scheduling in cloud environment which enables the
various cloud services to help framework implementation. Thus the far reaching way of different type of
scheduling algorithms in cloud computing environment surveyed which includes the workflow scheduling
and grid scheduling. The survey gives an elaborate idea about grid, cloud, workflow scheduling to
minimize the energy cost, efficiency and throughput of the system.
Optimization of energy consumption in cloud computing datacenters IJECEIAES
Cloud computing has emerged as a practical paradigm for providing IT resources, infrastructure and services. This has led to the establishment of datacenters that have substantial energy demands for their operation. This work investigates the optimization of energy consumption in cloud datacenter using energy efficient allocation of tasks to resources. The work seeks to develop formal optimization models that minimize the energy consumption of computational resources and evaluates the use of existing optimization solvers in testing these models. Integer linear programming (ILP) techniques are used to model the scheduling problem. The objective is to minimize the total power consumed by the active and idle cores of the servers’ CPUs while meeting a set of constraints. Next, we use these models to carry out a detailed performance comparison between a selected set of Generic ILP and 0-1 Boolean satisfiability based solvers in solving the ILP formulations. Simulation results indicate that in some cases the developed models have saved up to 38% in energy consumption when compared to common techniques such as round robin. Furthermore, results also showed that generic ILP solvers had superior performance when compared to SAT-based ILP solvers especially as the number of tasks and resources grow in size.
Hybrid Based Resource Provisioning in CloudEditor IJCATR
The data centres and energy consumption characteristics of the various machines are often noted with different capacities.
The public cloud workloads of different priorities and performance requirements of various applications when analysed we had noted
some invariant reports about cloud. The Cloud data centres become capable of sensing an opportunity to present a different program.
In out proposed work, we are using a hybrid method for resource provisioning in data centres. This method is used to allocate the
resources at the working conditions and also for the energy stored in the power consumptions. Proposed method is used to allocate the
process behind the cloud storage.
Energy efficient task scheduling algorithms for cloud data centerseSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Energy efficient task scheduling algorithms for cloud data centerseSAT Journals
Abstract Cloud computing is a modern technology which contains a network of systems that form a cloud. Energy conservation is one of the major concern in cloud computing. Large amount of energy is wasted by the computers and other devices and the carbon dioxide gas is released into the atmosphere polluting the environment. Green computing is an emerging technology which focuses on preserving the environment by reducing various kinds of pollutions. Pollutions include excessive emission of greenhouse gas, disposal of e-waste and so on leading to greenhouse effect. So pollution needs to be reduced by lowering the energy usage. By doing this, utilization of resources should not be reduced. With less usage of energy, maximum resource utilization should be possible. For this purpose, many green task scheduling algorithms are used so that the energy consumption can be minimized in servers of cloud data centers. In this paper, ESF-ES algorithm is developed which focuses on minimizing energy consumption by minimizing the number of servers used. The comparison is made with hybrid algorithms and most-efficient-server first scheme. Keywords: Cloud computing, Green computing, Energy-efficiency, Green data centers and Task scheduling.
Energy efficient task scheduling algorithms for cloud data centerseSAT Journals
Abstract
Life time of Wireless device Networks (WSNs) has perpetually been a important issue and has received enlarged attention within the
recent years. Typically wireless device nodes area unit equipped with low power batteries that area unit impossible to recharge.
Wireless device networks ought to have enough energy to satisfy the specified necessities of applications. during this paper, we have a
tendency to propose Energy economical Routing and Fault node Replacement (EERFNR) formula to extend the lifespan of wireless
device network, cut back information loss and conjointly cut back device node replacement value. Transmission drawback and device
node loading drawback is solved by adding many relay nodes and composition device node’s routing mistreatment stratified Gradient
Diffusion. The device node will save backup nodes to cut back the energy for re-looking the route once the device node routing is
broken. Genetic formula can calculate the device nodes to exchange, apply the foremost on the market routing methods to replace the
fewest device nodes.
Keywords: Genetic algorithmic rule, stratified gradient diffusion, grade diffusion, wireless device networks
Multi-objective load balancing in cloud infrastructure through fuzzy based de...IAESIJAI
Cloud computing became a popular technology which influence not only
product development but also made technology business easy. The services
like infrastructure, platform and software can reduce the complexity of
technology requirement for any ecosystem. As the users of cloud-based
services increases the complexity of back-end technologies also increased.
The heterogeneous requirement of users in terms for various configurations
creates different unbalancing issues related to load. Hence effective load
balancing in a cloud system with reference to time and space become crucial
as it adversely affect system performance. Since the user requirement and
expected performance is multi-objective use of decision-making tools like
fuzzy logic will yield good results as it uses human procedure knowledge in
decision making. The overall system performance can be further improved by
dynamic resource scheduling using optimization technique like genetic
algorithm.
An energy optimization with improved QOS approach for adaptive cloud resources IJECEIAES
In recent times, the utilization of cloud computing VMs is extremely enhanced in our day-to-day life due to the ample utilization of digital applications, network appliances, portable gadgets, and information devices etc. In this cloud computing VMs numerous different schemes can be implemented like multimedia-signal-processing-methods. Thus, efficient performance of these cloud-computing VMs becomes an obligatory constraint, precisely for these multimedia-signal-processing-methods. However, large amount of energy consumption and reduction in efficiency of these cloud-computing VMs are the key issues faced by different cloud computing organizations. Therefore, here, we have introduced a dynamic voltage and frequency scaling (DVFS) based adaptive cloud resource re-configurability (퐴퐶푅푅) technique for cloud computing devices, which efficiently reduces energy consumption, as well as perform operations in very less time. We have demonstrated an efficient resource allocation and utilization technique to optimize by reducing different costs of the model. We have also demonstrated efficient energy optimization techniques by reducing task loads. Our experimental outcomes shows the superiority of our proposed model 퐴퐶푅푅 in terms of average run time, power consumption and average power required than any other state-of-art techniques.
Cost-Efficient Task Scheduling with Ant Colony Algorithm for Executing Large ...Editor IJCATR
The aim of cloud computing is to share a large number of resources and pieces of equipment to compute and store knowledge and information for great scientific sources. Therefore, the scheduling algorithm is regarded as one of the most important challenges and problems in the cloud. To solve the task scheduling problem in this study, the ant colony optimization (ACO) algorithm was adapted from social theories with a fair and accurate resource allocation approach based on machine performance and capacity. This study was intended to decrease the runtime and executive costs. It was also meant to optimize the use of machines and reduce their idle time. Finally, the proposed method was compared with Berger and greedy algorithms. The simulation results indicate that the proposed algorithm reduced the makespan and executive cost when tasks were added. It also increased fairness and load balancing. Moreover, it made the optimal use of machines possible and increased user satisfaction. According to evaluations, the proposed algorithm improved the makespan by 80%.
Optimization of energy consumption in cloud computing datacenters IJECEIAES
Cloud computing has emerged as a practical paradigm for providing IT resources, infrastructure and services. This has led to the establishment of datacenters that have substantial energy demands for their operation. This work investigates the optimization of energy consumption in cloud datacenter using energy efficient allocation of tasks to resources. The work seeks to develop formal optimization models that minimize the energy consumption of computational resources and evaluates the use of existing optimization solvers in testing these models. Integer linear programming (ILP) techniques are used to model the scheduling problem. The objective is to minimize the total power consumed by the active and idle cores of the servers’ CPUs while meeting a set of constraints. Next, we use these models to carry out a detailed performance comparison between a selected set of Generic ILP and 0-1 Boolean satisfiability based solvers in solving the ILP formulations. Simulation results indicate that in some cases the developed models have saved up to 38% in energy consumption when compared to common techniques such as round robin. Furthermore, results also showed that generic ILP solvers had superior performance when compared to SAT-based ILP solvers especially as the number of tasks and resources grow in size.
Hybrid Based Resource Provisioning in CloudEditor IJCATR
The data centres and energy consumption characteristics of the various machines are often noted with different capacities.
The public cloud workloads of different priorities and performance requirements of various applications when analysed we had noted
some invariant reports about cloud. The Cloud data centres become capable of sensing an opportunity to present a different program.
In out proposed work, we are using a hybrid method for resource provisioning in data centres. This method is used to allocate the
resources at the working conditions and also for the energy stored in the power consumptions. Proposed method is used to allocate the
process behind the cloud storage.
Energy efficient task scheduling algorithms for cloud data centerseSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Energy efficient task scheduling algorithms for cloud data centerseSAT Journals
Abstract Cloud computing is a modern technology which contains a network of systems that form a cloud. Energy conservation is one of the major concern in cloud computing. Large amount of energy is wasted by the computers and other devices and the carbon dioxide gas is released into the atmosphere polluting the environment. Green computing is an emerging technology which focuses on preserving the environment by reducing various kinds of pollutions. Pollutions include excessive emission of greenhouse gas, disposal of e-waste and so on leading to greenhouse effect. So pollution needs to be reduced by lowering the energy usage. By doing this, utilization of resources should not be reduced. With less usage of energy, maximum resource utilization should be possible. For this purpose, many green task scheduling algorithms are used so that the energy consumption can be minimized in servers of cloud data centers. In this paper, ESF-ES algorithm is developed which focuses on minimizing energy consumption by minimizing the number of servers used. The comparison is made with hybrid algorithms and most-efficient-server first scheme. Keywords: Cloud computing, Green computing, Energy-efficiency, Green data centers and Task scheduling.
Energy efficient task scheduling algorithms for cloud data centerseSAT Journals
Abstract
Life time of Wireless device Networks (WSNs) has perpetually been a important issue and has received enlarged attention within the
recent years. Typically wireless device nodes area unit equipped with low power batteries that area unit impossible to recharge.
Wireless device networks ought to have enough energy to satisfy the specified necessities of applications. during this paper, we have a
tendency to propose Energy economical Routing and Fault node Replacement (EERFNR) formula to extend the lifespan of wireless
device network, cut back information loss and conjointly cut back device node replacement value. Transmission drawback and device
node loading drawback is solved by adding many relay nodes and composition device node’s routing mistreatment stratified Gradient
Diffusion. The device node will save backup nodes to cut back the energy for re-looking the route once the device node routing is
broken. Genetic formula can calculate the device nodes to exchange, apply the foremost on the market routing methods to replace the
fewest device nodes.
Keywords: Genetic algorithmic rule, stratified gradient diffusion, grade diffusion, wireless device networks
Multi-objective load balancing in cloud infrastructure through fuzzy based de...IAESIJAI
Cloud computing became a popular technology which influence not only
product development but also made technology business easy. The services
like infrastructure, platform and software can reduce the complexity of
technology requirement for any ecosystem. As the users of cloud-based
services increases the complexity of back-end technologies also increased.
The heterogeneous requirement of users in terms for various configurations
creates different unbalancing issues related to load. Hence effective load
balancing in a cloud system with reference to time and space become crucial
as it adversely affect system performance. Since the user requirement and
expected performance is multi-objective use of decision-making tools like
fuzzy logic will yield good results as it uses human procedure knowledge in
decision making. The overall system performance can be further improved by
dynamic resource scheduling using optimization technique like genetic
algorithm.
An energy optimization with improved QOS approach for adaptive cloud resources IJECEIAES
In recent times, the utilization of cloud computing VMs is extremely enhanced in our day-to-day life due to the ample utilization of digital applications, network appliances, portable gadgets, and information devices etc. In this cloud computing VMs numerous different schemes can be implemented like multimedia-signal-processing-methods. Thus, efficient performance of these cloud-computing VMs becomes an obligatory constraint, precisely for these multimedia-signal-processing-methods. However, large amount of energy consumption and reduction in efficiency of these cloud-computing VMs are the key issues faced by different cloud computing organizations. Therefore, here, we have introduced a dynamic voltage and frequency scaling (DVFS) based adaptive cloud resource re-configurability (퐴퐶푅푅) technique for cloud computing devices, which efficiently reduces energy consumption, as well as perform operations in very less time. We have demonstrated an efficient resource allocation and utilization technique to optimize by reducing different costs of the model. We have also demonstrated efficient energy optimization techniques by reducing task loads. Our experimental outcomes shows the superiority of our proposed model 퐴퐶푅푅 in terms of average run time, power consumption and average power required than any other state-of-art techniques.
Cost-Efficient Task Scheduling with Ant Colony Algorithm for Executing Large ...Editor IJCATR
The aim of cloud computing is to share a large number of resources and pieces of equipment to compute and store knowledge and information for great scientific sources. Therefore, the scheduling algorithm is regarded as one of the most important challenges and problems in the cloud. To solve the task scheduling problem in this study, the ant colony optimization (ACO) algorithm was adapted from social theories with a fair and accurate resource allocation approach based on machine performance and capacity. This study was intended to decrease the runtime and executive costs. It was also meant to optimize the use of machines and reduce their idle time. Finally, the proposed method was compared with Berger and greedy algorithms. The simulation results indicate that the proposed algorithm reduced the makespan and executive cost when tasks were added. It also increased fairness and load balancing. Moreover, it made the optimal use of machines possible and increased user satisfaction. According to evaluations, the proposed algorithm improved the makespan by 80%.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.