Authors:
Cheikhou Thiam
;
Georges Da-Costa
and
Jean-Marc Pierson
Affiliation:
Universite de Toulouse 3 Paul Sabatier, France
Keyword(s):
Energy, Virtual Machines, Cloud, Consolidation.
Related
Ontology
Subjects/Areas/Topics:
Algorithms for Reduced Power, Energy and Heat
;
Architectures for Smart Grids
;
Case Studies on Green Computing and Communications
;
Economic Models of Energy Efficiency
;
Energy and Economy
;
Energy Efficient Network Hardware
;
Energy Management Systems (EMS)
;
Energy Monitoring
;
Energy Profiling and Measurement
;
Energy-Aware Systems and Technologies
;
Energy-Efficient Communication Protocols
;
Evolutionary Algorithms in Energy Applications
;
Green Communications Architectures and Frameworks
;
Green Computing Models, Methodologies and Paradigms
;
Green Data Centers
;
Green Software Engineering Methodologies and Tools
;
Load Balancing in Smart Grids
;
Optimization Techniques for Efficient Energy Consumption
;
Qos and Green Computing
;
Scheduling and Switching Power Supplies
;
Smart Grids
;
Sustainable Computing and Communications
;
Virtualization for Reducing Power Consumption
;
Virtualization Impact for Green Computing
Abstract:
Cloud computing is a highly scalable and cost-effective infrastructure for running HPC, enterprise and Web
applications. However rapid growth of the demand for computational power by scientific, business and web-
applications has led to the creation of large-scale data centers consuming enormous amounts of electrical
power. Hence, energy-efficient solutions are required to minimize their energy consumption. The objective of
our approach is to reduce data center’s total energy consumption by controlling cloud applications’ overall resource usage while guarantying service level agreement. This article presents Energy aware clouds scheduling using anti-load balancing algorithm (EACAB). The proposed algorithm works by associating a credit value
with each node. The credit of a node depends on its affinity to its jobs, its current workload and its communication behavior. Energy savings are achieved by continuous consolidation of VMs according to current utilization of resources, virtual ne
twork topologies established between VMs and thermal state of computing
nodes. The experiment results show that the cloud application energy consumption and energy efficiency is
being improved effectively.
(More)