On the Use of Fuzzy Modeling in Virtualized Data Center Management

@article{Xu2007OnTU,
  title={On the Use of Fuzzy Modeling in Virtualized Data Center Management},
  author={Jing Xu and Ming Zhao and Jos{\'e} A. B. Fortes and Robert Carpenter and Mazin S. Yousif},
  journal={Fourth International Conference on Autonomic Computing (ICAC'07)},
  year={2007},
  pages={25-25}
}
  • J. XuMing Zhao M. Yousif
  • Published 11 June 2007
  • Computer Science
  • Fourth International Conference on Autonomic Computing (ICAC'07)
One of the most important goals of data-center management is to reduce cost through efficient use of resources. Virtualization techniques provide the opportunity of carving individual physical servers into multiple virtual containers that can be run and managed separately. A key challenge that comes with virtualization is the simultaneous on-demand provisioning of shared resources to virtual containers and the management of their capacities to meet service quality targets at the least cost… 
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References

SHOWING 1-10 OF 20 REFERENCES

Predictive Control for Dynamic Resource Allocation in Enterprise Data Centers

This paper studies the effect of prediction on dynamic resource allocation to virtualized servers running enterprise applications and presents predictive controllers using three different prediction algorithms based on a standard auto-regressive (AR) model, a combined ANOVA-AR model, as well as a multi-pulse (MP) model.

Utility-driven workload management using nested control design

This paper builds on earlier work on dynamic CPU allocation to applications on shared servers, and presents a feedback control system consisting of two nested integral control loops for managing the QoS metric of the application along with the utilization of the allocated CPU resource.

Adaptive entitlement control of resource containers on shared servers

By using the entitlement control system described, shared servers can potentially reach much higher resource utilization while meeting service level objectives for the hosted applications under changing operating conditions.

Configuring Workload Manager Control Parameters for Resource Pools

It is shown that by careful selection of workload scheduling parameters along with a proposed fast allocation policy the authors can sometimes more than triple the number of workloads that can be assigned to a pool without sacrificing application workload quality of service or the efficiency of the resource pool.

Utilization and SLO-Based Control for Dynamic Sizing of Resource Partitions

This paper identifies the nonlinear and bimodal properties of the models across different operating regions, and discusses their implications for the design of the control loops, and proposes two adaptive controllers for tracking the target utilization and target response time respectively.

Model-Based Resource Provisioning in a Web Service Utility

A new approach to utility resource management focusing on coordinated provisioning of memory and storage resources is presented, which incorporates internal models of service behavior to predict the value of candidate resource allotments under changing load.

Resource Allocation for Autonomic Data Centers using Analytic Performance Models

  • M. BennaniD. Menascé
  • Computer Science
    Second International Conference on Autonomic Computing (ICAC'05)
  • 2005
This paper presents a solution based on the use of analytic queuing network models combined with combinatorial search techniques to dynamically redeploy servers among the various AEs in order to optimize some global utility function.

Dynamic resource allocation for shared data centers using online measurements

A system architecture that combines online measurements with prediction and resource allocation techniques to react to changing workloads by dynamically varying the resource shares of applications and can handle nonlinearity in system behavior unlike some prior techniques.

Using fuzzy control to maximize profits in service level management

A profit-oriented feedback control system that automates the admission control decisions in a way that balances the loss of revenue due to rejected work against the penalties incurred if admitted work has excessive response times is proposed.

An analytical model for multi-tier internet services and its applications

This paper presents a model based on a network of queues, where the queues represent different tiers of the application, sufficiently general to capture the behavior of tiers with significantly different performance characteristics and application idiosyncrasies such as session-based workloads, concurrency limits, and caching at intermediate tiers.