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Proactive Management of Service Instance Pools for Meeting Service Level Agreements

  • Kavitha Ranganathan
  • Asit Dan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3826)

Abstract

Existing Grid schedulers focus on allocating resources to jobs as per the resource requirements expressed by end-users. This demands detailed knowledge of application behavior for different resource configurations on the part of end-users. Additionally, this model incurs significant delay in terms of the provisioning overhead for each request. In contrast, for interactive workloads, services are commonly pre-configured by an application server according to long-term steady-state requirements. In this paper, we propose a framework for bridging the gap between these two extremes. We target application services beyond simple interactive workloads, such as a parallel numeric application. In our approach, end users are shielded from lower-level resource configuration details and deal only with service metrics like average response time, expressed as SLAs. These SLAs are then translated into concrete resource allocation decisions. Since demand for a service fluctuates over time, static pre-configurations may not maximize utility of the common pool of resources. Our approach involves dynamic re-provisioning to achieve maximum utility, while accounting for overheads incurred during re-provisioning. We find that it is not always beneficial to re-provision resources according to perceived benefits and propose a model for calculating the optimal amount of re-provisioning for a particular scenario.

Keywords

Service Level Agreement Service Type Average Response Time Service Instance Incremental Adaptation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Kavitha Ranganathan
    • 1
  • Asit Dan
    • 1
  1. 1.IBM T J Watson Research CenterHawthorneUSA

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