Automated QoS-oriented cloud resource optimization using containers

Yu Sun, Jules White, Bo Li, Michael Walker, Hamilton Turner

Research output: Contribution to journalArticlepeer-review


Optimizing the deployment of software in a cloud environment is one approach for maximizing system Quality-of-Service (QoS) and minimizing total cost. A traditional challenge to this optimization is the large amount of benchmarking required to optimize even simplistic cloud systems. This paper introduces C 2RAM, an new approach to enable rapid, optimized deployment of software onto a cloud environment by substantially reducing the number of benchmarks required. C 2RAM continues to perform some benchmarking, and therefore its predictions of application QoS metrics, such as throughput and latency, are very accurate. Our results show a maximum difference of 1.06 % between C 2RAM predicted QoS and empirically measured QoS. Moreover, C 2RAM can be provided with QoS requirements for each software in the system, and will ensure that each requirement is met before presenting a deployment plan.

Original languageEnglish (US)
Pages (from-to)101-137
Number of pages37
JournalAutomated Software Engineering
Issue number1
StatePublished - Mar 1 2017
Externally publishedYes


  • Automated software deployment
  • Bin packing
  • QoS performance
  • Resource allocation and optimization

ASJC Scopus subject areas

  • Software


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