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An efficient job management of computing service using integrated idle VM resources for high-performance computing based on OpenStack

  • Seok-Hyeon Han
  • Hyun-Woo Kim
  • Young-Sik JeongEmail author
Article
  • 6 Downloads

Abstract

In recent years, various studies on OpenStack-based high-performance computing have been conducted. OpenStack combines off-the-shelf physical computing devices and creates a resource pool of logical computing. The configuration of the logical computing resource pool provides computing infrastructure according to the user’s request and can be applied to the infrastructure as a service (laaS), which is a cloud computing service model. The OpenStack-based cloud computing can provide various computing services for users using a virtual machine (VM). However, intensive computing service requests from a large number of users during large-scale computing jobs may delay the job execution. Moreover, idle VM resources may occur and computing resources are wasted if users do not employ the cloud computing resources. To resolve the computing job delay and waste of computing resources, a variety of studies are required including computing task allocation, job scheduling, utilization of idle VM resource, and improvements in overall job’s execution speed according to the increase in computing service requests. Thus, this paper proposes an efficient job management of computing service (EJM-CS) by which idle VM resources are utilized in OpenStack and user’s computing services are processed in a distributed manner. EJM-CS logically integrates idle VM resources, which have different performances, for computing services. EJM-CS improves resource wastes by utilizing idle VM resources. EJM-CS takes multiple computing services rather than single computing service into consideration. EJM-CS determines the job execution order considering workloads and waiting time according to job priority of computing service requester and computing service type, thereby providing improved performance of overall job execution when computing service requests increase.

Keywords

OpenStack Job management Idle VM resources High-performance computing Computing service Distributed computing Cloud computing 

Notes

Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1A09000631).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Multimedia EngineeringDongguk UniversitySeoulRepublic of Korea

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