The Community for Technology Leaders
Green Image
Issue No. 05 - Sept.-Oct. (2013 vol. 10)
ISSN: 1545-5971
pp: 253-272
Li Zhang , IBM Thomas J. Watson Research Center, Yorktown Heights
Mark S. Squillante , IBM Thomas J. Watson Research Center, Yorktown Heights
Danilo Ardagna , Politecnico di Milano, Milan
Barbara Panicucci , Politecnico di Milano, Milan and Università di Modena e Reggio Emilia, Reggio Emilia
Bernardetta Addis , Università degli Studi di Torino, Torino
Worldwide interest in the delivery of computing and storage capacity as a service continues to grow at a rapid pace. The complexities of such cloud computing centers require advanced resource management solutions that are capable of dynamically adapting the cloud platform while providing continuous service and performance guarantees. The goal of this paper is to devise resource allocation policies for virtualized cloud environments that satisfy performance and availability guarantees and minimize energy costs in very large cloud service centers. We present a scalable distributed hierarchical framework based on a mixed-integer nonlinear optimization of resource management acting at multiple timescales. Extensive experiments across a wide variety of configurations demonstrate the efficiency and effectiveness of our approach.
Servers, Resource management, Optimization, Availability, Quality of service, Load management, Radio spectrum management, virtualized system QoS-based migration policies, Performance attributes, performance of systems, quality concepts, optimization of cloud configurations, QoS-based scheduling and load balancing
Li Zhang, Mark S. Squillante, Danilo Ardagna, Barbara Panicucci, Bernardetta Addis, "A Hierarchical Approach for the Resource Management of Very Large Cloud Platforms", IEEE Transactions on Dependable and Secure Computing, vol. 10, no. , pp. 253-272, Sept.-Oct. 2013, doi:10.1109/TDSC.2013.4
93 ms
(Ver )