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OptiSpot: minimizing application deployment cost using spot cloud resources.

Daniel J Dubois1, Giuliano Casale1

  • 1Department of Computing, Imperial College London, London, UK.

Cluster Computing
|February 4, 2020
PubMed
Summary
This summary is machine-generated.

OptiSpot automates cloud application deployment on spot instances, optimizing resource selection and pricing bids. This heuristic minimizes costs while ensuring performance, outperforming traditional methods.

Keywords:
Application deploymentBidding strategyCloud provisioningFluid-approximated queueing networksRandom environmentSpot cloud

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Area of Science:

  • Computer Science
  • Cloud Computing
  • Operations Research

Background:

  • Cloud providers offer virtual machines via a spot instance model, where resources are sold to the highest bidder.
  • Fluctuating spot prices can lead to customers losing rented virtual machines due to overbidding.

Purpose of the Study:

  • To propose OptiSpot, a heuristic algorithm for automating application deployment decisions in cloud environments utilizing the spot pricing model.
  • To determine optimal resource allocation, component mapping, and spot price bidding strategies for cost minimization and performance assurance.

Main Methods:

  • Combines a multi-class queueing network model of the application with a Markov model of spot price dynamics and virtual machine reliability.
  • Evaluates the heuristic using a model of a real enterprise application and historical Amazon EC2 spot instance pricing data.

Main Results:

  • OptiSpot successfully identifies low-cost deployment solutions that maintain acceptable application performance levels.
  • The heuristic method demonstrates significantly faster convergence to low-cost optimal solutions compared to nonlinear programming techniques.

Conclusions:

  • OptiSpot provides an effective automated approach for managing cloud application deployments on spot instances.
  • The proposed heuristic offers a practical and efficient solution for optimizing cloud resource utilization and reducing costs.