BROWSE

Related Researcher

Author's Photo

Baek, Woongki
Intelligent System Software Lab (ISSL)
Research Interests
  • System software, machine-learning systems, parallel and distributed systems, computer systems security

ITEM VIEW & DOWNLOAD

Holistic VM Placement for Distributed Parallel Applications in Heterogeneous Clusters

DC Field Value Language
dc.contributor.author Kim, Seontae ko
dc.contributor.author Pham, Nguyen ko
dc.contributor.author Baek, Woongki ko
dc.contributor.author Choi, Young-Ri ko
dc.date.available 2019-10-04T00:44:55Z -
dc.date.created 2019-09-29 ko
dc.date.issued 2021-09 ko
dc.identifier.citation IEEE TRANSACTIONS ON SERVICES COMPUTING, v.14, no.5, pp.1411 - 1425 ko
dc.identifier.issn 1939-1374 ko
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/27799 -
dc.description.abstract In a heterogeneous cluster, virtual machine (VM) placement for a distributed parallel application is challenging due to numerous possible ways of placing the application and complexity of estimating the performance of the application. This study investigates a holistic VM placement technique for distributed parallel applications in a heterogeneous cluster, aiming to maximize the efficiency of the cluster and consequently reduce the costs for service providers and users. The proposed technique accommodates various factors that have an impact on performance in a combined manner. First, we analyze the effects of the heterogeneity of resources, different VM configurations, and interference between VMs on the performance of distributed parallel applications with a wide diversity of characteristics, including scientific and big data analytics applications. We then propose a placement technique that uses a machine learning algorithm to estimate the runtime of a distributed parallel application. To train a performance estimation model, a distributed parallel application is profiled against synthetic workloads that mostly utilize the dominant resource of the application, which strongly affects the application performance, reducing the profiling space dramatically. Through experimental and simulation studies, we show that the proposed placement technique can find good VM placement configurations for various workloads. ko
dc.language 영어 ko
dc.publisher IEEE COMPUTER SOC ko
dc.title Holistic VM Placement for Distributed Parallel Applications in Heterogeneous Clusters ko
dc.type ARTICLE ko
dc.identifier.scopusid 2-s2.0-85074858649 ko
dc.identifier.wosid 000704110400012 ko
dc.type.rims ART ko
dc.identifier.doi 10.1109/TSC.2018.2890668 ko
dc.identifier.url https://ieeexplore.ieee.org/document/8598959 ko
Appears in Collections:
CSE_Journal Papers

find_unist can give you direct access to the published full text of this article. (UNISTARs only)

Show simple item record

qrcode

  • mendeley

    citeulike

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

MENU