An Energy-Aware VMs Placement Algorithm in Cloud Computing Environment

2012 ◽  
Author(s):  
Xiaoli Wang ◽  
Zhanghui Liu
Keyword(s):  
Cloud Computing ◽  
Computing Environment ◽  
Energy Aware ◽  
Cloud Computing Environment ◽  
Placement Algorithm

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

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>

scholarly journals Optimization Algorithms based Task Scheduling Method for Cloud Computing Environment

2019 ◽  
Vol 8 (3) ◽  
pp. 3608-3613
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Large Scale ◽  
Data Centers ◽  
Computing Environment ◽  
Energy Aware ◽  
Cloud Computing Environment ◽  
Scheduling Method ◽  
Consistent Performance ◽  
Computing Structure

There are various enhancements in the world of technology. Among that Cloud computing delivers numerous amenities over the Internet. It employs data centers which comprise hardware and software provision for loading, servers, and systems. The primary reason for the popularity of Cloud computing is consistent performance, economical operation, prompt accessibility, rapid scaling and much more. The chief cause for concern in cloud computing are the errors that happen either in the software or the hardware and energy consumption on a large scale. The clients pay only for resources utilized by them and assets which are accessible during the computing in a cloud setting. In the environment of cloud computing, Task scheduling is significant concepts which can be used to minimize the energy and time spent. The algorithms in Task scheduling might employ various measures toward dispense preference to subtasks that may generate many schedules to the divergent computing structure. Moreover, consumption of energy could be dissimilar for every source which is allocated to a job. This present research explores that the PSO-CA based energy aware task scheduling method can predict with the aim to enhance the resource distribution.

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