Green and Energy-Efficient Computing Architecture for E-Learning

2016 ◽  
pp. 252-277
Author(s):  
K. Palanivel ◽  
S. Kuppuswami
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Data Centers ◽  
Critical Issue ◽  
Green Computing ◽  
Cloud Infrastructure ◽  
Computing Architecture ◽  
Energy Efficient Computing ◽  
E Learning

Information and Communication Technology (ICT) is one of the fast growing industries that facilitate many latest services to the users and therefore, the number of users is increasing rapidly. The usage of ICT and its life cycle produce hazardous substances that need to be addressed in efficient and green ways. The adoption of green computing involves many improvements and provide energy-efficiency services for data centers, power management and cloud computing. Cloud computing is a highly scalable and cost-effective infrastructure for running Web applications. However, the growing demand of Cloud infrastructure has drastically increased the energy consumption of data centers, which has become a critical issue. Hence, energy-efficient solutions are required to minimize the impact of Cloud environment. E-learning methodology is an example of Green computing. Thus, it is proposed a Green Cloud Computing Architecture for e-Learning Applications that can lower expenses and reduce energy consumption.

Green and Energy-Efficient Computing Architecture for E-Learning

2016 ◽  
pp. 1668-1692 ◽  
Author(s):  
K. Palanivel ◽  
S. Kuppuswami
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Data Centers ◽  
Critical Issue ◽  
Green Computing ◽  
Cloud Infrastructure ◽  
Computing Architecture ◽  
Energy Efficient Computing ◽  
E Learning

Information and Communication Technology (ICT) is one of the fast growing industries that facilitate many latest services to the users and therefore, the number of users is increasing rapidly. The usage of ICT and its life cycle produce hazardous substances that need to be addressed in efficient and green ways. The adoption of green computing involves many improvements and provide energy-efficiency services for data centers, power management and cloud computing. Cloud computing is a highly scalable and cost-effective infrastructure for running Web applications. However, the growing demand of Cloud infrastructure has drastically increased the energy consumption of data centers, which has become a critical issue. Hence, energy-efficient solutions are required to minimize the impact of Cloud environment. E-learning methodology is an example of Green computing. Thus, it is proposed a Green Cloud Computing Architecture for e-Learning Applications that can lower expenses and reduce energy consumption.

Energy-Efficiency in Cloud Data Centers

2013 ◽  
pp. 241-263
Author(s):  
Burak Kantarci ◽  
Hussein T. Mouftah
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Data Center ◽  
Energy Efficient ◽  
Large Scale ◽  
Data Centers ◽  
High Energy ◽  
It Services ◽  
Data Center Network ◽  
Cloud Data

Cloud computing aims to migrate IT services to distant data centers in order to reduce the dependency of the services on the limited local resources. Cloud computing provides access to distant computing resources via Web services while the end user is not aware of how the IT infrastructure is managed. Besides the novelties and advantages of cloud computing, deployment of a large number of servers and data centers introduces the challenge of high energy consumption. Additionally, transportation of IT services over the Internet backbone accumulates the energy consumption problem of the backbone infrastructure. In this chapter, the authors cover energy-efficient cloud computing studies in the data center involving various aspects such as: reduction of processing, storage, and data center network-related power consumption. They first provide a brief overview of the existing approaches on cool data centers that can be mainly grouped as studies on virtualization techniques, energy-efficient data center network design schemes, and studies that monitor the data center thermal activity by Wireless Sensor Networks (WSNs). The authors also present solutions that aim to reduce energy consumption in data centers by considering the communications aspects over the backbone of large-scale cloud systems.

scholarly journals Energy Efficiency Analysis Between Green Computing and Cloud Computing

2019 ◽  
Vol 8 (3S2) ◽  
pp. 254-258
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Data Center ◽  
Energy Efficient ◽  
Green Computing ◽  
Energy Efficient Computing ◽  
Green Data Center ◽  
Computer Resources ◽  
Server System ◽  
Energy Efficiency Analysis

Usually cloud computing is based under effective data computing but green cloud computing focus on energy efficiency of device and computing mainly based on computing architecture. Here cloud computing is also known as green computing due its better effective energy. The purpose of green computing is to decrease the usage of harmful resources, maximizing energy efficiency throughout the living span of the good and also to promote the recyclability or bio degradability of useless goods plus misuse materials of the factory. In order to simulate the hardware by utilizing software, green computing plays a major role for various technologies like virtualization, green data center, cloud and grid computing and power optimization. Here computer resources are effectively utilized by replacing the data center standalone server system by artificial server so as to run the software by less number for large computers called as virtualized. Finally this paper is fulfilled by the advancement of recognized energy efficient computing

scholarly journals An Event Diminishment Model to Optimize Cloud Environment

2020 ◽  
Vol 9 (4) ◽  
pp. 744-749
Keyword(s):  
Sustainable Development ◽  
Cloud Computing ◽  
Data Centers ◽  
Scale Up ◽  
Critical Issue ◽  
It Services ◽  
Cloud Infrastructure ◽  
Cloud Data ◽  
Carbon Dioxide Gas ◽  
Cloud Data Centers

Cloud computing is to compute a task assigned to a set of connections, software and services that can be utilized by the user over a network. The trending need of Cloud infrastructure has drastically scale up the energy need of data centers, which has become a critical issue. In the row also lead to high carbon emission which is not environment friendly so there is a need of energy efficient approach in cloud computing The research paper aims to reach a theoretical notion of sustainable development with proposing an incentive for reducing global warming through effective clustering techniques and methods. This paper aims to reduce cloud events by applying map reduce on large event clusters formed in cloud. The purpose of the paper is to develop a better methodology for handling the events of cloud computing and possibly clustering and reducing the similar types of events. This approach might lead to the reduction of carbon-dioxide gas (which is a greenhouse gas) by less usage of servers in cloud data centers. With the advent of IT services in cloud computing energy consumption it is necessary for the developing technology to progress towards sustainable development rather thrashing and harnessing energy from every possible means.

Green Cloud Computing

2018 ◽  
pp. 114-136
Author(s):  
Indira K. ◽  
Thangavel M.
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Web Applications ◽  
Performance Metrics ◽  
Cost Effective ◽  
Critical Issue ◽  
Efficient Solutions ◽  
Cloud Infrastructure ◽  
Total Energy Consumption ◽  
Green Cloud

Cloud computing is a highly scalable and cost-effective infrastructure for running HPC, enterprise and Web applications. However, the growing demand of Cloud infrastructure has drastically increased the energy consumption of data centers, which has become a critical issue. High energy consumption not only translates to high operational cost, which reduces the profit margin of Cloud providers, but also leads to high carbon emissions which is not environmentally friendly. Hence, energy-efficient solutions are required to minimize the impact of Cloud computing on the environment. Thus, in this chapter, we discuss various elements of Green Clouds which contribute to the total energy consumption. The chapter also explains the role of Green Cloud Performance metrics and Green Cloud Architecture.

scholarly journals Energy Efficient and VM Consolidation Framework using Improved Spider Monkey Optimization Algorithm

2021 ◽  
Vol 10 (3) ◽  
pp. 21-26
Author(s):  
Kethavath Prem Kumar ◽  
◽  
Thirumalaisamy Ragunathan ◽  
Devara Vasumathi ◽  
◽  
...  
Keyword(s):  
Cloud Computing ◽  
Energy Efficient ◽  
Data Centers ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Energy Usage ◽  
Energy Efficient Computing ◽  
Spider Monkey Optimization ◽  
Vm Consolidation

Cloud Computing is rapidly being utilized to operate informational technological services by outstanding technologies for a variety of benefits, including dynamically improved resources planning and a new service delivery method. The Cloud computing process is occurred by allowing the client devices for data access through the internet from a remote server, computers, and the databases. An internet connection is linked among the front end users such as client device, network, browser, and software application with the back end that constitutes of servers, computers, and database. For satisfying the demands of the Service Level Agreement (SLA), providers of cloud service should reduce the usage of energy. Capacity reservations oriented system is available by clouds’ providers to permit users for customizing Virtual Machines (VMs) having specified age and geographic resources, reduces the amount to be paid for cloud services. To overcome the aforementioned issue, an Improved Spider Monkey Optimization (ISMO) approach is proposed for cloud center optimization. The VM consolidation architecture based on the proposed ISMO algorithm decreases energy usage while attempting to prevent Service Level Agreement breaches. The accessibility of hosts or virtual machines (VMs) for task performance is measured by fitness. If the number of tasks to be handled increases the hosts of VMs available at right state. The proposed VM consolidation architecture decreases energy usage while also attempting to prevent Service Level Agreement breaches and also provide energy-efficient computing in data centers. The proposed approach may be utilized to provide energy-efficient computing in data centers. The energy efficiency of the proposed ISMO method is achieved 28266 whereas, the existing algorithm showed an energy efficiency of 6009 and 10001.

scholarly journals Survey on Energy Efficiency in Cloud Computing

2019 ◽  
Vol 8 (1) ◽  
pp. 18-21
Author(s):  
Lakshmi Digra ◽  
Sharanjeet Singh
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Data Center ◽  
Energy Efficient ◽  
Large Scale ◽  
Data Centers ◽  
Energy Requirements ◽  
International Level ◽  
German Data

Data centers are serious, energy-hungry infrastructures that can run large scale Internet based services. Energy ingesting representations are essential in designing and improving energy-efficient operations to reduce excessive energy consumption in data centers. This paper presents a survey on Energy efficiency in data centers, importance of energy efficiency. It also describes the increasing demands for data center in worldwide and the reasons for data centers energy inefficient? In this paper we define the challenges for implementing changes in data centers and explain why and how the energy requirements of data centers are growing. After that we compare the German data center market at international level and we see the energy consumption of data centers and servers in Germany from 2010 -2016.

scholarly journals Independent Task Scheduling in Heterogeneous System

2019 ◽  
Vol 8 (4) ◽  
pp. 10093-10099
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Task Scheduling ◽  
Rapid Development ◽  
Network Connectivity ◽  
Variable Number ◽  
Cloud Infrastructure ◽  
Storage Devices ◽  
Quantum Genetic Algorithm ◽  
Test Scenarios

Recently, the rapid development in processing speeds, fast storage devices and better network connectivity, hasaccelerated the popularization of cloud computing. Cloud computing is an on-demand-servicewhich provides users with high end servers,storage and processing capabilities where the user need not be concerned with its infrastructure.Although, there are abundant resources in the cloud infrastructure, for the efficient working and execution of tasks, task scheduling plays a crucial role. Task scheduling results in better performance (throughput) of the system along with better resource utilization which ultimately results inreduced energy consumption. At any given time, a processor should never be in idle state, as it still consumes some amount of energy. In this paper, the use of Quantum Genetic Algorithm has led to the reduction in energy consumption. The objective is to find a scheduling sequencewhich can be implemented ina cloud computing environment. Along with minimizing energy consumption, the algorithm helps reduce makespan time of a processor as well.The results show a decrease in energy consumption by 10-15% under different test scenarios involving a variable number of tasks, processors, and the number of iterations (generations) for which the algorithm was run. The algorithm converges to the desired result within 10-15 iterations, as can be seen from the results published in this paper.

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