loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock
Towards Combining Reactive and Proactive Cloud Elasticity on Running HPC Applications

Topics: Framework (conceptual, logical or software); IaaS, PaaS and SaaS, Big Data and Analytics demonstrations and Research Discussions from Computing Scientists, Business IS Academics and Industrial Consultants; Scheduling, Service Duplication, Fairness, Load Balance for SaaS and Analytics; System Design and Architecture

Authors: Vinicius Facco Rodrigues 1 ; Rodrigo da Rosa Righi 1 ; Cristiano André da Costa 1 ; Dhananjay Singh 2 ; Víctor Mendez Munoz 3 and Victor Chang 4

Affiliations: 1 Universidade do Vale do Rio dos Sinos (UNISINOS), Brazil ; 2 Hankuk Univeristy of Foreign Studies (HUFS), Korea, Republic of ; 3 Autonomous University of Barcelona, Spain ; 4 Xi’an Jiaotong Liverpool University, China

ISBN: 978-989-758-296-7

Keyword(s): Cloud Utility, High-performance Computing, Live Thresholding, Resource Management, Self-organizing.

Abstract: The elasticity feature of cloud computing has been proved as pertinent for parallel applications, since users do not need to take care about the best choice for the number of processes/resources beforehand. To accomplish this, the most common approaches use threshold-based reactive elasticity or time-consuming proactive elasticity. However, both present at least one problem related to: the need of a previous user experience, lack on handling load peaks, completion of parameters or design for a specific infrastructure and workload setting. In this regard, we developed a hybrid elasticity service for parallel applications named SelfElastic. As parameterless model, SelfElastic presents a closed control loop elasticity architecture that adapts at runtime the values of lower and upper thresholds. Besides presenting SelfElastic, our purpose is to provide a comparison with our previous work on reactive elasticity called AutoElastic. The results present the SelfElastic’s lightweight feature, besides highlighting its performance competitiveness in terms of application time and cost metrics. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.238.70.175

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Facco Rodrigues, V.; Righi, R.; André da Costa, C.; Singh, D.; Munoz, V. and Chang, V. (2018). Towards Combining Reactive and Proactive Cloud Elasticity on Running HPC Applications.In Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-296-7, pages 261-268. DOI: 10.5220/0006761302610268

@conference{iotbds18,
author={Vinicius Facco Rodrigues. and Rodrigo da Rosa Righi. and Cristiano André da Costa. and Dhananjay Singh. and Víctor Mendez Munoz. and Victor Chang.},
title={Towards Combining Reactive and Proactive Cloud Elasticity on Running HPC Applications},
booktitle={Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2018},
pages={261-268},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006761302610268},
isbn={978-989-758-296-7},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - Towards Combining Reactive and Proactive Cloud Elasticity on Running HPC Applications
SN - 978-989-758-296-7
AU - Facco Rodrigues, V.
AU - Righi, R.
AU - André da Costa, C.
AU - Singh, D.
AU - Munoz, V.
AU - Chang, V.
PY - 2018
SP - 261
EP - 268
DO - 10.5220/0006761302610268

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.