A distributed cloud resource management framework for High-Performance Computing (HPC) applications

Kannan Govindarajan, Vivekanandan Suresh Kumar, Thamarai Selvi Somasundaram

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

9 Citations (Scopus)

Abstract

The High-Performance Computing (HPC) users require the high-end compute, storage, and, network execution environment in a dynamic manner for testing HPC applications. The High-Performance Computing Cloud (HPCC) provides a kind of execution environment in an on-demand manner. Generally, the cloud resource management system or cloud resource broker manages the compute, storage, and network resources in HPCC. However, it faces the challenges of scalability, interoperability, and achieving guaranteed Quality of Service (QoS). Hence, the proposed research work addresses the above-said issues by employing the distributed cloud resource management framework. The proposed system can be able to handle a large number of user application requests and manage the multiple cloud resources in an interoperable manner. The proposed system is evaluated by submitting a large number of real-world HPC applications. The performance metrics such as response time, a number of successfully handled requests, and user satisfaction are measured to evaluate the performance of proposed system.

Original languageEnglish
Title of host publication2016 8th International Conference on Advanced Computing, ICoAC 2016
Pages1-6
Number of pages6
ISBN (Electronic)9781509058884
DOIs
Publication statusPublished - 16 Jun. 2017
Event8th International Conference on Advanced Computing, ICoAC 2016 - Chennai, India
Duration: 19 Jan. 201721 Jan. 2017

Publication series

Name2016 8th International Conference on Advanced Computing, ICoAC 2016

Conference

Conference8th International Conference on Advanced Computing, ICoAC 2016
Country/TerritoryIndia
CityChennai
Period19/01/1721/01/17

Keywords

  • Cloud Computing
  • Distributed Hash Table (DHT)
  • Distributed Resource Management
  • High-Performance Computing
  • Semantic Description and Discovery

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