A New Model for Energy Consumption Optimization under Cloud Computing and its Genetic Algorithm

2014 ◽  
Author(s):  
Hai Zhu ◽  
Xiaoli Wang ◽  
Hongfeng Wang
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Energy Consumption ◽  
New Model ◽  
Energy Consumption Optimization

scholarly journals THE ADVANTAGE OF GENETIC ALGORITHM IN ENERGY-EFFICIENT SCHEDULING FOR HETEROGENEOUS CLOUD COMPUTING

2016 ◽  
Vol 4 (7) ◽  
pp. 1-9
Author(s):  
Hang Zhou ◽  
Samina Kausar ◽  
Ningning Dong
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Scheduling Problem ◽  
New Energy ◽  
Heavy Burden ◽  
Heterogeneous Cloud ◽  
Energy Efficient Scheduling ◽  
Computing Infrastructure

Nowadays Energy Consumption has been a heavy burden on the enterprise cloud computing infrastructure. This paper focuses on the hardware factors in energy consumption. Inspired by DVFS, it proposes a new energy-efficient (EE) model. This paper formulates the scheduling problem and genetic algorithm is applied to obtain higher efficiency value. Simulations are implemented to verify the advantage of genetic algorithm. In addition, the robustness of our strategy is validated by modifying the relevant parameters of the experiment.

scholarly journals Multi-objective hybrid genetic algorithm for task scheduling problem in cloud computing

2021 ◽  
Author(s):  
Poria Pirozmand ◽  
Ali Asghar Rahmani Hosseinabadi ◽  
Maedeh Farrokhzad ◽  
Mehdi Sadeghilalimi ◽  
Seyedsaeid Mirkamali ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Scheduling Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Computing System ◽  
Computing Systems ◽  
Cloud Computing System ◽  
Scheduling Heuristic ◽  
The Cost

AbstractThe cloud computing systems are sorts of shared collateral structure which has been in demand from its inception. In these systems, clients are able to access existing services based on their needs and without knowing where the service is located and how it is delivered, and only pay for the service used. Like other systems, there are challenges in the cloud computing system. Because of a wide array of clients and the variety of services available in this system, it can be said that the issue of scheduling and, of course, energy consumption is essential challenge of this system. Therefore, it should be properly provided to users, which minimizes both the cost of the provider and consumer and the energy consumption, and this requires the use of an optimal scheduling algorithm. In this paper, we present a two-step hybrid method for scheduling tasks aware of energy and time called Genetic Algorithm and Energy-Conscious Scheduling Heuristic based on the Genetic Algorithm. The first step involves prioritizing tasks, and the second step consists of assigning tasks to the processor. We prioritized tasks and generated primary chromosomes, and used the Energy-Conscious Scheduling Heuristic model, which is an energy-conscious model, to assign tasks to the processor. As the simulation results show, these results demonstrate that the proposed algorithm has been able to outperform other methods.

Research on Technology of Energy Consumption Optimization in Cloud Computing Platform

2015 ◽  
Vol 713-715 ◽  
pp. 2467-2470
Author(s):  
Liang Hao ◽  
Gang Cui ◽  
Ming Cheng Qu ◽  
Wen De Ke
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Global Climate ◽  
Economic Benefits ◽  
Optimization Techniques ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Computing Platform ◽  
Energy Consumption Optimization ◽  
Cloud Computing Platform

With the shortage of energy and global climate warming, as well as the low-carbon economy and green computing coming, the energy consumption of cloud computing has become a critical issue, and even the economic benefits of cloud computing has been widely discussion. In view of the phenomenon of energy is wasted seriously in cloud computing, the energy optimization techniques in cloud computing platform have been studied and summarized in this paper. The concept, characteristics and development of cloud computing are introduced firstly. And then the existing energy consumption optimization approaches of cloud computing are studied deeply. The opening and closing techniques, dynamic voltage adjustment technology, virtual energy-saving technology and resource scheduling optimization technology are studied deeply. Finally, the contents are summarized and the future is looked forward.

Sign in / Sign up

Export Citation Format

Share Document