Authors:
Cheikhou Thiam
1
;
Georges Da Costa
2
and
Jean-Marc Pierson
2
Affiliations:
1
Universite de Thiés, Senegal
;
2
IRIT, Toulouse Computer Science Institute and Toulouse University, France
Keyword(s):
Energy, Heuristic, Virtual Machines, Cloud federation, Migration.
Related
Ontology
Subjects/Areas/Topics:
Algorithms for Reduced Power, Energy and Heat
;
Energy and Economy
;
Energy Management Systems (EMS)
;
Energy-Aware Systems and Technologies
;
Evolutionary Algorithms in Energy Applications
;
Optimization Techniques for Efficient Energy Consumption
;
Sustainable Computing and Communications
;
Virtualization for Reducing Power Consumption
Abstract:
In Cloud Computing, scheduling jobs is a major and difficult issue. The main objectives of cloud services providers are the efficient use of their computing resources. Existing cloud management systems are mostly based on centralized architectures and energy management mechanisms are suffering several limitations. To address these limitations, our contribution is to design, implement, and evaluate a novel cloud management system which provides a holistic energy-efficient VM management solution by integrating advanced VM management mechanisms such as underload mitigation, VM consolidation, and power management. In this paper, we introduce a distributed task scheduling algorithm for Clouds that enables to schedule VMs cooperatively and dynamically inside a federation of clouds. We evaluated our prototype through simulations, to compare our decentralized approach with a centralized one. Our results showed that the proposed scheduler is very reactive.