A New Energy Efficient VM Scheduling Algorithm for Cloud Computing Based on Dynamic Programming

2017 ◽  
Author(s):  
Kepi Zhang ◽  
Tong Wu ◽  
Siyuan Chen ◽  
Linsen Cai ◽  
Chao Peng
Keyword(s):  
Cloud Computing ◽  
Dynamic Programming ◽  
Energy Efficient ◽  
Scheduling Algorithm ◽  
Vm Scheduling ◽  
New Energy

Energy-efficient collaborative optimization for VM scheduling in cloud computing

2021 ◽  
pp. 108565
Author(s):  
Bin Wang ◽  
Fagui Liu ◽  
Weiwei Lin ◽  
Zhenjiang Ma ◽  
Dishi Xu
Keyword(s):  
Cloud Computing ◽  
Energy Efficient ◽  
Collaborative Optimization ◽  
Vm Scheduling

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 Energy-Efficient Multi-Job Scheduling Model for Cloud Computing and Its Genetic Algorithm

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Xiaoli Wang ◽  
Yuping Wang ◽  
Hai Zhu
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Energy Efficient ◽  
Job Scheduling ◽  
Point Of View ◽  
Scheduling Model ◽  
Fitness Value ◽  
New Energy ◽  
Searching Ability ◽  
Local Search Operator

For the problem that the energy efficiency of the cloud computing data center is low, from the point of view of the energy efficiency of the servers, we propose a new energy-efficient multi-job scheduling model based on Google’s massive data processing framework. To solve this model, we design a practical encoding and decoding method for the individuals and construct an overall energy efficiency function of the servers as the fitness value of each individual. Meanwhile, in order to accelerate the convergent speed of our algorithm and enhance its searching ability, a local search operator is introduced. Finally, the experiments show that the proposed algorithm is effective and efficient.

scholarly journals An Energy-Efficient Hybrid Scheduling Algorithm for Task Scheduling in the Cloud Computing Environments

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 117325-117337
Author(s):  
Navpreet Kaur Walia ◽  
Navdeep Kaur ◽  
Majed Alowaidi ◽  
Kamaljeet Singh Bhatia ◽  
Shailendra Mishra ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Energy Efficient ◽  
Scheduling Algorithm ◽  
Hybrid Scheduling ◽  
Computing Environments
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