Tetris: Optimizing cloud resource usage unbalance with elastic VM

Xiao Ling, Yi Yuan, Dan Wang, Jiahai Yang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)


Recently, the cloud systems face an increasing number of big data applications. It becomes an important issue for the cloud providers to allocate resources so as to accommodate as many of these big data applications as possible. In current cloud service, e.g., Amazon EMR, a job runs on a fixed cluster. This means that a fixed amount of resources (e.g. CPU, memory) is allocated to the life cycle of this job. We observe that the resources are inefficiently used in such services because of resources usage unbalance. Therefore, we propose a runtime elastic VM approach where the cloud system can increase or decrease the number of CPUs at different time periods for the jobs. There is little change to such services as Amazon EMR, yet the cloud system can accommodate many more jobs. In this paper, we first present a measurement study to show the feasibility and the quantitative impact of adjusting VM configurations dynamically. We then model the task and job completion time of big data applications, which are used for elastic VM adjustment decisions. We validate our models through experiments. We present Tetris, an elastic VM strategy based on cloud system that can better optimize resource utilization to support big data applications. We further implement a Tetris prototype and comprehensively evaluate Tetris on a real private cloud platform using Facebook trace and Wikipedia dataset. We observe that with Tetris, the cloud system can accommodate 31.3% more jobs.
Original languageEnglish
Title of host publication2016 IEEE/ACM 24th International Symposium on Quality of Service, IWQoS 2016
ISBN (Electronic)9781509026340
Publication statusPublished - 13 Oct 2016
Event24th IEEE/ACM International Symposium on Quality of Service, IWQoS 2016 - Beijing, China
Duration: 20 Jun 201621 Jun 2016


Conference24th IEEE/ACM International Symposium on Quality of Service, IWQoS 2016

ASJC Scopus subject areas

  • Management of Technology and Innovation
  • Computer Networks and Communications
  • Media Technology
  • Safety, Risk, Reliability and Quality


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