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Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud
المؤلفون المشاركون
Zia Ullah, Qazi
Hassan, Shahzad
Khan, Gul Muhammad
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-07-25
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Infrastructure as a Service (IaaS) cloud provides resources as a service from a pool of compute, network, and storage resources.
Cloud providers can manage their resource usage by knowing future usage demand from the current and past usage patterns of resources.
Resource usage prediction is of great importance for dynamic scaling of cloud resources to achieve efficiency in terms of cost and energy consumption while keeping quality of service.
The purpose of this paper is to present a real-time resource usage prediction system.
The system takes real-time utilization of resources and feeds utilization values into several buffers based on the type of resources and time span size.
Buffers are read by R language based statistical system.
These buffers’ data are checked to determine whether their data follows Gaussian distribution or not.
In case of following Gaussian distribution, Autoregressive Integrated Moving Average (ARIMA) is applied; otherwise Autoregressive Neural Network (AR-NN) is applied.
In ARIMA process, a model is selected based on minimum Akaike Information Criterion (AIC) values.
Similarly, in AR-NN process, a network with the lowest Network Information Criterion (NIC) value is selected.
We have evaluated our system with real traces of CPU utilization of an IaaS cloud of one hundred and twenty servers.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zia Ullah, Qazi& Hassan, Shahzad& Khan, Gul Muhammad. 2017. Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1140976
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zia Ullah, Qazi…[et al.]. Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1140976
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zia Ullah, Qazi& Hassan, Shahzad& Khan, Gul Muhammad. Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1140976
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1140976
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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