Optimal markovian dynamic control of interference-prone server farms

Scott Votke, Jazeem Abdul Jaleel, Amoghavarsha Suresh, Mohammad Delasay, Sherwin Doroudi, Anshul Gandhi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Interference is a key performance challenge faced by cloud users, and can significantly degrade application performance on virtual machines (VMs). For load-balanced cloud applications, a key question is how to distribute the load among VMs in the presence of interference. Using a Markov decision process (MDP) model, we investigate dynamic control polices to assign jobs among a cluster of VMs that are prone to interference in a system with a central queue and an arbitrary number of VMs. We characterize the structural properties of the MDP optimality equation, and we prove that the optimal control policy is a threshold policy based on the queue length. The optimal policy is characterized by multiple thresholds depending on the current conditions of the VMs, including the number of busy under-interference VMs. We discuss the existence of an ordering among such thresholds, and we prove the ordering for a two-VM system. Our numerical results show that the optimal dynamic policy can significantly improve performance compared to the the commonly employed non-idling policy. For low utilization systems, we observe improvements on the order of around 20%. We further implement the optimal policy in a real-world testbed using the HAProxy load balancer, and show that it can reduce web server response times by as much as 40%-60%, even for time-varying request rates.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2019
PublisherIEEE Computer Society
Pages295-308
Number of pages14
ISBN (Electronic)9781728149509
DOIs
StatePublished - Oct 2019
Event27th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2019 - Rennes, France
Duration: Oct 22 2019Oct 25 2019

Publication series

NameProceedings - IEEE Computer Society's Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS
Volume2019-October
ISSN (Print)1526-7539

Conference

Conference27th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2019
CountryFrance
CityRennes
Period10/22/1910/25/19

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was supported by NSF CNS grants 1617046, 1717588, and 1750109.

Keywords

  • Cloud Computing
  • Markov Chains
  • Markov Decision Process
  • Optimal Control of Queues

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