Performance modeling and workflow scheduling of microservice-based applications in clouds

Liang Bao, Chase Wu, Xiaoxuan Bu, Nana Ren, Mengqing Shen

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Microservice has been increasingly recognized as a promising architectural style for constructing large-scale cloud-based applications within and across organizational boundaries. This microservice-based architecture greatly increases application scalability, but meanwhile incurs an expensive performance overhead, which calls for a careful design of performance modeling and task scheduling. However, these problems have thus far remained largely unexplored. In this paper, we develop a performance modeling and prediction method for independent microservices, design a three-layer performance model for microservice-based applications, formulate a Microservice-based Application Workflow Scheduling problem for minimum end-to-end delay under a user-specified Budget Constraint (MAWS-BC), and propose a heuristic microservice scheduling algorithm. The performance modeling and prediction method are validated and justified by experimental results generated through a well-known microservice benchmark on disparate computing nodes, and the performance superiority of the proposed scheduling solution is illustrated by extensive simulation results in comparison with existing algorithms.

Original languageEnglish (US)
Article number8651324
Pages (from-to)2101-2116
Number of pages16
JournalIEEE Transactions on Parallel and Distributed Systems
Volume30
Issue number9
DOIs
StatePublished - Sep 1 2019

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics

Keywords

  • Microservice
  • cloud computing
  • performance modeling and prediction
  • task scheduling

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