Using latency to evaluate interactive system performance
OSDI '96 Proceedings of the second USENIX symposium on Operating systems design and implementation
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Distributed Systems: Principles and Paradigms
Distributed Systems: Principles and Paradigms
Xen and the art of virtualization
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Defining and Monitoring Service-Level Agreements for Dynamic e-Business
LISA '02 Proceedings of the 16th USENIX conference on System administration
Designing controllable computer systems
HOTOS'05 Proceedings of the 10th conference on Hot Topics in Operating Systems - Volume 10
Adaptive control of virtualized resources in utility computing environments
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
Comparison of the three CPU schedulers in Xen
ACM SIGMETRICS Performance Evaluation Review
Running Xen: A Hands-On Guide to the Art of Virtualization
Running Xen: A Hands-On Guide to the Art of Virtualization
HPCC '08 Proceedings of the 2008 10th IEEE International Conference on High Performance Computing and Communications
Cloud Computing: Web-Based Applications That Change the Way You Work and Collaborate Online
Cloud Computing: Web-Based Applications That Change the Way You Work and Collaborate Online
SLA-Driven Semantically-Enhanced Dynamic Resource Allocator for Virtualized Service Providers
ESCIENCE '08 Proceedings of the 2008 Fourth IEEE International Conference on eScience
VCONF: a reinforcement learning approach to virtual machines auto-configuration
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
Virtual Business Operating Environment in the Cloud: Conceptual Architecture and Challenges
ER '09 Proceedings of the 28th International Conference on Conceptual Modeling
A control theory foundation for self-managing computing systems
IEEE Journal on Selected Areas in Communications
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A high-quality service for applications in cloud computing environments is guaranteed by making efficient use of resources in data centers. Applications should be allocated to resources suitable for the load of data centers to achieve this. The complex and dynamic nature of the load prevents the proper selection of one of multiple data centers and fails to meet the demands of resources in applications. An incorrect data center selection seriously lowers resource utilization in the data center and accordingly deteriorates the quality of services for applications. This paper proposes a neuro-fuzzy inference-based prediction scheme to select one of multiple data centers in accordance with application workloads. This scheme is used to aggressively capture the time-varying load of data centers by learning and predicting the availability of resources therein. Therefore, it predicts not only the present load but also the future load of data centers in the process of determining a suitable data center. By an autonomic control for data center selection, our scheme can also provide load balancing between data centers. Moreover, we present performance evaluations with experiments based on Xen testbeds to demonstrate the effectiveness of our scheme. The experimental results show that our scheme is superior to other selection schemes with regard to the entire and changed loads of data centers.