research-article

HPC Supported Mission-Critical Cloud Architecture

Authors:

Myong Hwan Yoo,

Seung Young Lee,

Kyuoke YeunAuthors Info & Claims

ICPE '17: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering

Pages 223 - 232

https://doi.org/10.1145/3030207.3044531

Published: 17 April 2017 Publication History

Abstract

Tactical Operations Center (TOC) system in military field is an advanced computer system composed of multiple servers and desktops to interlock internal/external weapon systems processing mission-critical applications in combat situation. However, the current TOC system has several limitations such as difficulty of integrating tactical weapon systems including missile launch system and radar system into the single TOC system due to the heterogeneity of HW and SW between systems, and an inefficient computing resource management for the weapon systems.

In this paper, we proposed a novel HPC supported mission-critical Cloud architecture as TOC for Surface-to-Air-Missile (SAM) system with OpenStack Cloud OS, Data Distribution Service (DDS), and GPU virtualization techniques. With this approach, our system provides elastic resource management over the weapon systems with virtual machines, integration of heterogeneous systems with different kinds of guest OS, real-time, reliable, and high-speed communication between the virtual machines and virtualized GPU resource over the virtual machines. Evaluation of our TOC system includes DDS performance measurement over 10Gbps Ethernet and QDR InfiniBand networks on the virtualized environment with OpenStack Cloud OS, and GPU virtualization performance evaluation with two different methods, PCI pass-through and remote-API. With the evaluation results, we conclude that our system provides reasonable performance in the combat situation compared to the previous TOC system while additionally supports scalable and elastic use of computing resource through the virtual machines.

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Cited By

Kang DJun TKim DKim JKim D(2017)ConVGPU: GPU Management Middleware in Container Based Virtualized Environment2017 IEEE International Conference on Cluster Computing (CLUSTER)10.1109/CLUSTER.2017.17(301-309)Online publication date: Sep-2017
https://doi.org/10.1109/CLUSTER.2017.17

Index Terms

HPC Supported Mission-Critical Cloud Architecture

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Published In

cover image ACM Conferences

ICPE '17: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering

April 2017

450 pages

ISBN:9781450344043

DOI:10.1145/3030207

General Chairs:
Walter Binder
Università della Svizzera Italiana, Switzerland
,
Vittorio Cortellessa
Università dell'Aquila, Italy
,
Program Chairs:
Anne Koziolek
Karlsruhe Institute of Technology, Germany
,
Evgenia Smirni
College of William & Mary, USA
,
Meikel Poess
Oracle Corporation, USA

Copyright © 2017 ACM.

© 2017 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
SIGSOFT: ACM Special Interest Group on Software Engineering
SPEC: SPEC Research Group

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 April 2017

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ICPE '17: ACM/SPEC International Conference on Performance Engineering

April 22 - 26, 2017

L'Aquila, Italy

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ICPE '17 Paper Acceptance Rate 27 of 83 submissions, 33%;

Overall Acceptance Rate 252 of 851 submissions, 30%

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Cited By

Kang DJun TKim DKim JKim D(2017)ConVGPU: GPU Management Middleware in Container Based Virtualized Environment2017 IEEE International Conference on Cluster Computing (CLUSTER)10.1109/CLUSTER.2017.17(301-309)Online publication date: Sep-2017
https://doi.org/10.1109/CLUSTER.2017.17

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