Energy-Efficient Task Consolidation for Cloud Data Center

Energy saving in a Cloud Computing environment is a multidimensional challenge, which can directly decrease the in-use costs and carbon dioxide emission, while raising the system consistency. The process of maximizing the cloud computing resource utilization which brings many benefits such as better use of resources, rationalization of maintenance, IT service customization, QoS and reliable services, etc., is known as task consolidation. This article suggests the energy saving with task consolidation, by minimizing the number of unused resources in a cloud computing environment. In this article, various task consolidation algorithms such as MinIncreaseinEnergy, MaxUtilECTC, NoIdleMachineECTC, and NoIdleMachineMaxUtil are presented aims to optimize energy consumption of cloud data center. The outcomes have shown that the suggested algorithms surpass the existing ECTC and FCFSMaxUtil, MaxMaxUtil algorithms in terms of the CPU utilization and energy consumption.

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A Comprehensive Study of Security in Cloud Computing

Advances in Wireless Technologies and Telecommunication - Handbook of Research on Advanced Wireless Sensor Network Applications, Protocols, and Architectures ◽

10.4018/978-1-5225-0486-3.ch016 ◽

2017 ◽

pp. 386-412

Author(s):

Prasanta K. Manohari ◽

Niranjan K. Ray

Keyword(s):

Cloud Computing ◽

Data Center ◽

Emerging Technology ◽

Security Risk ◽

Computing Environment ◽

Cloud Data Center ◽

Cloud Computing Environment ◽

Cloud Computing Security ◽

Cloud Data ◽

Security Issues

Cloud computing is one of the emerging technology in the recent times which has varieties of applications at different fields. It is an Internet dependent technology and it store and maintain the data in a cloud data center. Cloud center usually supports more numbers of user, applications and data. In the same time, it also suffered with numerous challenges. Security is a key requirement for cloud data center. Different security mechanisms are proposed for cloud computing environment. In this chapter, we address the background of cloud computing, security risk, requirements, issues, and some of the security techniques are discussed. We discuss different security issues and focus on some existing solutions.

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A Comprehensive Study of Security in Cloud Computing

Cyber Security and Threats ◽

10.4018/978-1-5225-5634-3.ch003 ◽

2018 ◽

pp. 27-53

Author(s):

Prasanta K. Manohari ◽

Niranjan K. Ray

Keyword(s):

Cloud Computing ◽

Data Center ◽

Emerging Technology ◽

Security Risk ◽

Computing Environment ◽

Cloud Data Center ◽

Cloud Computing Environment ◽

Cloud Computing Security ◽

Cloud Data ◽

Security Issues

Cloud computing is one of the emerging technology in the recent times which has varieties of applications at different fields. It is an Internet dependent technology and it store and maintain the data in a cloud data center. Cloud center usually supports more numbers of user, applications and data. In the same time, it also suffered with numerous challenges. Security is a key requirement for cloud data center. Different security mechanisms are proposed for cloud computing environment. In this chapter, we address the background of cloud computing, security risk, requirements, issues, and some of the security techniques are discussed. We discuss different security issues and focus on some existing solutions.

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Research on Cloud Computing Environment Energy Saving Optimization Method

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1049-1050.2122 ◽

2014 ◽

Vol 1049-1050 ◽

pp. 2122-2125

Author(s):

Hong Li Li

Keyword(s):

Energy Efficiency ◽

Cloud Computing ◽

Energy Saving ◽

Data Center ◽

Optimization Method ◽

Computing Environment ◽

Computing Technology ◽

Cloud Computing Environment

In this paper, the background of cloud computing technology to study how to optimize cloud computing data center energy efficiency mechanisms. This paper analyzes the DVFS energy saving strategy, virtualization energy saving strategy, turn off / on energy saving strategies, such as the current mainstream strategy, comparing different energy saving strategies have not applied scenes.

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An Energy-Efficient Resource Scheduling Algorithm for Cloud Computing based on Resource Equivalence Optimization

International Journal of Grid and High Performance Computing ◽

10.4018/ijghpc.2016040103 ◽

2016 ◽

Vol 8 (2) ◽

pp. 43-57 ◽

Cited By ~ 14

Author(s):

Li Mao ◽

De Yu Qi ◽

Wei Wei Lin ◽

Bo Liu ◽

Ye Da Li

Keyword(s):

Resource Allocation ◽

Cloud Computing ◽

Energy Consumption ◽

Data Center ◽

Energy Efficient ◽

Resource Scheduling ◽

Constraint Satisfaction Problems ◽

Cloud Data Center ◽

Cloud Data ◽

Efficient Resource

With the rapid growth of energy consumption in global data centers and IT systems, energy optimization has become an important issue to be solved in cloud data center. By introducing heterogeneous energy constraints of heterogeneous physical servers in cloud computing, an energy-efficient resource scheduling model for heterogeneous physical servers based on constraint satisfaction problems is presented. The method of model solving based on resource equivalence optimization is proposed, in which the resources in the same class are pruning treatment when allocating resource so as to reduce the solution space of the resource allocation model and speed up the model solution. Experimental results show that, compared with DynamicPower and MinPM, the proposed algorithm (EqPower) not only improves the performance of resource allocation, but also reduces energy consumption of cloud data center.

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Minimizing Energy Consumption by Task Consolidation in Cloud Centers with Optimized Resource Utilization

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v6i6.pp3283-3292 ◽

2016 ◽

Vol 6 (6) ◽

pp. 3283 ◽

Cited By ~ 1

Author(s):

Mahendra Kumar Gourisaria ◽

S. S. Patra ◽

P. M. Khilar

Keyword(s):

Cloud Computing ◽

Energy Consumption ◽

Power Consumption ◽

Resource Utilization ◽

Data Centers ◽

Carbon Dioxide Emission ◽

Computing Environment ◽

Energy Aware ◽

Cloud Computing Environment ◽

Cpu Utilization

<p>Cloud computing is an emerging field of computation. As the data centers consume large amount of power, it increases the system overheads as well as the carbon dioxide emission increases drastically. The main aim is to maximize the resource utilization by minimizing the power consumption. However, the greatest usages of resources does not mean that there has been a right use of energy. Various resources which are idle, also consumes a significant amount of energy. So we have to keep minimum resources idle. Current studies have shown that the power consumption due to unused computing resources is nearly 1 to 20%. So, the unused resources have been assigned with some of the tasks to utilize the unused period. In the present paper, it has been suggested that the energy saving with task consolidation which has been saved the energy by minimizing the number of idle resources in a cloud computing environment. It has been achieved far-reaching experiments to quantify the performance of the proposed algorithm. The same has also been compared with the FCFSMaxUtil and Energy aware Task Consolidation (ETC) algorithm. The outcomes have shown that the suggested algorithm surpass the FCFSMaxUtil and ETC algorithm in terms of the CPU utilization and energy consumption.</p>

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Minimizing Energy Consumption by Task Consolidation in Cloud Centers with Optimized Resource Utilization

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v6i6.12251 ◽

2016 ◽

Vol 6 (6) ◽

pp. 3283

Author(s):

Mahendra Kumar Gourisaria ◽

S. S. Patra ◽

P. M. Khilar

Keyword(s):

Cloud Computing ◽

Energy Consumption ◽

Power Consumption ◽

Resource Utilization ◽

Data Centers ◽

Carbon Dioxide Emission ◽

Computing Environment ◽

Energy Aware ◽

Cloud Computing Environment ◽

Cpu Utilization

<p>Cloud computing is an emerging field of computation. As the data centers consume large amount of power, it increases the system overheads as well as the carbon dioxide emission increases drastically. The main aim is to maximize the resource utilization by minimizing the power consumption. However, the greatest usages of resources does not mean that there has been a right use of energy. Various resources which are idle, also consumes a significant amount of energy. So we have to keep minimum resources idle. Current studies have shown that the power consumption due to unused computing resources is nearly 1 to 20%. So, the unused resources have been assigned with some of the tasks to utilize the unused period. In the present paper, it has been suggested that the energy saving with task consolidation which has been saved the energy by minimizing the number of idle resources in a cloud computing environment. It has been achieved far-reaching experiments to quantify the performance of the proposed algorithm. The same has also been compared with the FCFSMaxUtil and Energy aware Task Consolidation (ETC) algorithm. The outcomes have shown that the suggested algorithm surpass the FCFSMaxUtil and ETC algorithm in terms of the CPU utilization and energy consumption.</p>

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Building Energy Consumption Data Index Method in Cloud Computing Environment

International Journal of Performability Engineering ◽

10.23940/ijpe.20.05.p8.747756 ◽

2020 ◽

Vol 16 (5) ◽

pp. 747

Author(s):

Liang Yuan ◽

Cheng Hongfang ◽

Chen Wangshun

Keyword(s):

Cloud Computing ◽

Energy Consumption ◽

Building Energy ◽

Building Energy Consumption ◽

Computing Environment ◽

Index Method ◽

Cloud Computing Environment ◽

Consumption Data

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Multidimensional Resource Scheduling in Cloud Data Centers

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1008-1009.1513 ◽

2014 ◽

Vol 1008-1009 ◽

pp. 1513-1516

Author(s):

Hai Na Song ◽

Xiao Qing Zhang ◽

Zhong Tang He

Keyword(s):

Cloud Computing ◽

Data Centers ◽

Bin Packing ◽

Virtual Machines ◽

Three Dimensional ◽

Resource Scheduling ◽

Computing Environment ◽

Cloud Computing Environment ◽

Cloud Data ◽

Cloud Data Centers

Cloud computing environment is regarded as a kind of multi-tenant computing mode. With virtulization as a support technology, cloud computing realizes the integration of multiple workloads in one server through the package and seperation of virtual machines. Aiming at the contradiction between the heterogeneous applications and uniform shared resource pool, using the idea of bin packing, the multidimensional resource scheduling problem is analyzed in this paper. We carry out some example analysis in one-dimensional resource scheduling, two-dimensional resource schduling and three-dimensional resource scheduling. The results shows that the resource utilization of cloud data centers will be improved greatly when the resource sheduling is conducted after reorganizing rationally the heterogeneous demands.

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Opportunities and Challenges of Data Migration in Cloud

Engineering International ◽

10.18034/ei.v9i1.529 ◽

2021 ◽

Vol 9 (1) ◽

pp. 41-50

Author(s):

Ruhul Amin ◽

Siddhartha Vadlamudi

Keyword(s):

Cloud Computing ◽

Impact Analysis ◽

Academic Research ◽

Security Requirements ◽

Data Migration ◽

Cloud Provider ◽

Computing Environment ◽

Cloud Computing Environment ◽

Cloud Data ◽

Cloud Migration

Cloud data migration is the process of moving data, localhost applications, services, and data to the distributed cloud processing framework. The success of this data migration measure is relying upon a few viewpoints like planning and impact analysis of existing enterprise systems. Quite possibly the most widely recognized process is moving locally stored data in a public cloud computing environment. Cloud migration comes along with both challenges and advantages, so there are different academic research and technical applications on data migration to the cloud that will be discussed throughout this paper. By breaking down the research achievement and application status, we divide the existing migration techniques into three strategies as indicated by the cloud service models essentially. Various processes should be considered for different migration techniques, and various tasks will be included accordingly. The similarities and differences between the migration strategies are examined, and the challenges and future work about data migration to the cloud are proposed. This paper, through a research survey, recognizes the key benefits and challenges of migrating data into the cloud. There are different cloud migration procedures and models recommended to assess the presentation, identifying security requirements, choosing a cloud provider, calculating the expense, and making any essential organizational changes. The results of this research paper can give a roadmap for data migration and can help decision-makers towards a secure and productive migration to a cloud computing environment.

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