Multiobjective Energy-Aware Workflow Scheduling in Distributed Datacenters

2016 ◽  
pp. 79-93 ◽  
Author(s):  
Sergio Nesmachnow ◽  
Santiago Iturriaga ◽  
Bernabé Dorronsoro ◽  
Andrei Tchernykh
Keyword(s):  
Workflow Scheduling ◽  
Energy Aware

Energy-Aware Workflow Scheduling in Grid Under QoS Constraints

2015 ◽  
Vol 41 (2) ◽  
pp. 495-511 ◽  
Author(s):  
Ritu Garg ◽  
Awadhesh Kumar Singh
Keyword(s):  
Workflow Scheduling ◽  
Energy Aware

scholarly journals Multi-Objective Approach for Energy-Aware Workflow Scheduling in Cloud Computing Environments

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Sonia Yassa ◽  
Rachid Chelouah ◽  
Hubert Kadima ◽  
Bertrand Granado
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Heterogeneous Computing ◽  
Pso Algorithm ◽  
Workflow Scheduling ◽  
Energy Aware ◽  
Multi Objective ◽  
Traditional Research ◽  
Dynamic Voltage

We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service) requirements. Traditional research in workflow scheduling mainly focuses on the optimization constrained by time or cost without paying attention to energy consumption. The main contribution of this study is to propose a new approach for multi-objective workflow scheduling in clouds, and present the hybrid PSO algorithm to optimize the scheduling performance. Our method is based on the Dynamic Voltage and Frequency Scaling (DVFS) technique to minimize energy consumption. This technique allows processors to operate in different voltage supply levels by sacrificing clock frequencies. This multiple voltage involves a compromise between the quality of schedules and energy. Simulation results on synthetic and real-world scientific applications highlight the robust performance of the proposed approach.

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