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Cluster Computing

Erschienen in:

21.11.2016

ACCRS: autonomic based cloud computing resource scaling

verfasst von: Ziad A. Al-Sharif, Yaser Jararweh, Ahmad Al-Dahoud, Luay M. Alawneh

Erschienen in: Cluster Computing | Ausgabe 3/2017

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Abstract

A cloud computing model gives cloud service providers the ability to retain multiple workloads on a single physical system. However, efficient resource provisioning and possible system fault management in the cloud can be a challenge. Early fault detection can provide room to recover from potential faults before impacting QoS. Current static techniques of fault management in computing systems are not satisfactory enough to safeguard the QoS requested by cloud users. Thus, new smart techniques are needed. This paper presents the ACCRS framework for cloud computing infrastructures to advance system’s utilization level, reduce cost and power consumption and fulfil SLAs. The ACCRS framework employs Autonomic Computing basic components which includes state monitoring, planning, decision making, fault predication, detection, and root cause analysis for recovery actions to improve system’s reliability, availability, and utilization level by scaling resources in response to changes in the cloud system state.

Vorheriger Artikel Reactive performance monitoring of Cloud computing environments

Nächster Artikel Recent advancements in resource allocation techniques for cloud computing environment: a systematic review

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Titel: ACCRS: autonomic based cloud computing resource scaling
verfasst von: Ziad A. Al-Sharif
Yaser Jararweh
Ahmad Al-Dahoud
Luay M. Alawneh
Publikationsdatum: 21.11.2016
Verlag: Springer US
Erschienen in: Cluster Computing / Ausgabe 3/2017
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-016-0682-6

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