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Adaptive Prediction Models for Data Center Resources Utilization Estimation

Shuja-ur-Rehman Baig, Waheed Iqbal, Josep Lluis Berral, Abdelkarim Erradi, David Carrera
2019 IEEE Transactions on Network and Service Management  
To address these problems, we propose a novel method to adaptively and automatically identify the most appropriate model to accurately estimate data center resources utilization.  ...  The proposed approach trains a classifier based on statistical features of historical resources usage to decide the appropriate prediction model to use for given resource utilization observations collected  ...  modeling and predicting data center resource utilization.  ... 
doi:10.1109/tnsm.2019.2932840 fatcat:3bbu3n6pqrbt5kuxbcqfazrufq

Adaptive sliding windows for improved estimation of data center resource utilization

Shuja-ur-Rehman Baig, Waheed Iqbal, Josep Lluis Berral, David Carrera
2019 Future generations computer systems  
Accurate prediction of data center resource utilization is required for capacity planning, job scheduling, energy saving, workload placement, and load balancing to utilize the resources efficiently.  ...  estimation model for each trend period.  ...  an estimation model for future resource utilization estimation.  ... 
doi:10.1016/j.future.2019.10.026 fatcat:bcpejkx5njesdi6djvfkgad3ba

workload forecasting and resource management models based on machine learning for cloud computing environments [article]

Deepika Saxena, Ashutosh Kumar Singh
2021 arXiv   pre-print
In this context, the paper presents a comprehensive survey of workload forecasting and predictive resource management models in cloud environment.  ...  A conceptual framework for workload forecasting and resource management, categorization of existing machine learning based resources allocation techniques, and major challenges of inefficient distribution  ...  Figure 1 : Typical resource utilization at cloud data center It clearly shows the resource under-utilization and overload events during typical resource capacity of a data center.  ... 
arXiv:2106.15112v1 fatcat:cngak4jdvzhjlpfa4jibfne23m

Auto-scaling Web Applications in Clouds: A Taxonomy and Survey [article]

Chenhao Qu, Rodrigo N. Calheiros, Rajkumar Buyya
2017 arXiv   pre-print
Web application providers have been migrating their applications to cloud data centers, attracted by the emerging cloud computing paradigm. One of the appealing features of the cloud is elasticity.  ...  It allows cloud users to acquire or release computing resources on-demand, which enables web application providers to automatically scale the resources provisioned to their applications without human intervention  ...  Yaser Mansouri, Xunyun Liu, Minxian Xu, and Bowen Zhou for their valuable comments and suggestions in improving the quality of the paper.  ... 
arXiv:1609.09224v6 fatcat:dkk2ftpvpbcnvhcmc6lz2omwa4

Power consumption prediction in cloud data center using machine learning

Deepika T., Prakash P.
2020 International Journal of Electrical and Computer Engineering (IJECE)  
Power consumption by cloud data centers is one of the crucial issues for service providers in the domain of cloud computing.  ...  Pursuant to the rapid technology enhancements in cloud environments and data centers augmentations, power utilization in data centers is expected to grow unabated.  ...  ., [12] proposed a self-adaptive differential evolution algorithm to estimate the workload utilized by the cloud data center using NASA trace and Saskatchewan trace.  ... 
doi:10.11591/ijece.v10i2.pp1524-1532 fatcat:ye6osztehzcohkohfu4pqn5axm

Virtual Machine Provisioning Based on Analytical Performance and QoS in Cloud Computing Environments

Rodrigo N. Calheiros, Rajiv Ranjan, Rajkumar Buyya
2011 2011 International Conference on Parallel Processing  
We model the behavior and performance of applications and Cloud-based IT resources to adaptively serve end-user requests.  ...  In this paper, we present a provisioning technique that automatically adapts to workload changes related to applications for facilitating the adaptive management of system and offering endusers guaranteed  ...  Fig. 1 . 1 Proposed mechanism for adaptive virtual machine provisioning. Fig. 2 . 2 Queueing model for the data center.  ... 
doi:10.1109/icpp.2011.17 dblp:conf/icpp/CalheirosRB11 fatcat:4kpouxz4g5dd5iwktyr2k4dmfq

Dynamic resource allocation for shared data centers using online measurements

Abhishek Chandra, Weibo Gong, Prashant Shenoy
2003 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems - SIGMETRICS '03  
data centers.  ...  The parameters of this model are continuously updated using an online monitoring and prediction framework. Our prediction technique is based on an autoregressive stochastic process model.  ...  data centers.  ... 
doi:10.1145/781064.781067 fatcat:yrg3vkrbyjhhngrpbyi337kjs4

Dynamic Resource Allocation for Shared Data Centers Using Online Measurements [chapter]

Abhishek Chandra, Weibo Gong, Prashant Shenoy
2003 Lecture Notes in Computer Science  
data centers.  ...  The parameters of this model are continuously updated using an online monitoring and prediction framework. Our prediction technique is based on an autoregressive stochastic process model.  ...  data centers.  ... 
doi:10.1007/3-540-44884-5_21 fatcat:plycwalgoncwlpv3nxgiymxkza

Dynamic resource allocation for shared data centers using online measurements

Abhishek Chandra, Weibo Gong, Prashant Shenoy
2003 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems - SIGMETRICS '03  
data centers.  ...  The parameters of this model are continuously updated using an online monitoring and prediction framework. Our prediction technique is based on an autoregressive stochastic process model.  ...  data centers.  ... 
doi:10.1145/781027.781067 dblp:conf/sigmetrics/ChandraGS03 fatcat:ifdrunxxu5gdfo4ufdqbyjokwe

Dynamic resource allocation for shared data centers using online measurements

Abhishek Chandra, Weibo Gong, Prashant Shenoy
2003 Performance Evaluation Review  
data centers.  ...  The parameters of this model are continuously updated using an online monitoring and prediction framework. Our prediction technique is based on an autoregressive stochastic process model.  ...  data centers.  ... 
doi:10.1145/885651.781067 fatcat:xztykx7i5rambm5mijugxrsvpq

Predictive Control for Dynamic Resource Allocation in Enterprise Data Centers

Wei Xu, Xiaoyun Zhu, S. Singhal, Zhikui Wang
2006 2006 IEEE/IFIP Network Operations and Management Symposium NOMS 2006  
We compare the properties of the predictive controllers with an adaptive integral (I) controller designed in our earlier work on controlling relative utilization of resource containers.  ...  The controllers are evaluated in a hypothetical virtual server environment where we use the CPU utilization traces collected on 36 servers in an enterprise data center.  ...  For the purpose of our study, we consider CPU utilization information from 48 servers in an enterprise data center.  ... 
doi:10.1109/noms.2006.1687544 dblp:conf/noms/XuZSW06 fatcat:tntkcok3hjeprm3ufciiovurne

Energy-Efficient Resource Allocation and Provisioning Framework for Cloud Data Centers

Mehiar Dabbagh, Bechir Hamdaoui, Mohsen Guizani, Ammar Rayes
2015 IEEE Transactions on Network and Service Management  
This paper proposes an integrated energy-aware resource provisioning framework for cloud data centers.  ...  The proposed framework: i) predicts the number of virtual machine (VM) requests, to be arriving at cloud data centers in the near future, along with the amount of CPU and memory resources associated with  ...  Note that initially both adaptive and static models give the same predictions as the adaptive model still has not made many updates.  ... 
doi:10.1109/tnsm.2015.2436408 fatcat:cjsycsh4pzb3pnzfyjm4otcn5q

Adaptive Resource Utilization Prediction System for Infrastructure as a Service Cloud

Qazi Zia Ullah, Shahzad Hassan, Gul Muhammad Khan
2017 Computational Intelligence and Neuroscience  
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 system takes real-time utilization of resources and feeds utilization values into several buffers based on the type of resources and time span size.  ...  In this paper, we apply an adaptive system for resource utilization prediction of IaaS cloud.  ... 
doi:10.1155/2017/4873459 pmid:28811819 pmcid:PMC5547731 fatcat:rwhas2nopverphkfsv5lp55c2q

Energy Consumption Modeling and Prediction in the Cloud Data Centers

Sara Diouani, Research Foundation for Development and Innovation in Science and Engineering, Casablanca, Morocco, Hicham Medromi
2020 Journal of Engineering Science and Technology Review  
In this context, we present different formulas for calculating energy consumption in cloud data centers and we propose a simplified and completed deduced formula for energy consumption estimation  ...  Various methods aimed to enhance the energy efficiency in data centers have been developed in the field related to the development of resource allocation.  ...  , modeling, and prediction for data center energy consumption.  ... 
doi:10.25103/jestr.133.25 fatcat:or6u4yy4hjhqzpalruq43zqjgi

Cloud Infrastructure Estimation and Auto-scaling using Recurrent Cartesian Genetic Programming based ANN

Qazi Zia Ullah, Gul Muhammad Khan, Shahzad Hassan
2020 IEEE Access  
The resource monitor takes resource utilizations and feeds to the estimator for efficient estimation of resources.  ...  This increase in cloud resource usage, leads to enormous amounts of energy consumption by cloud data center servers. Energy can be conserved in a cloud server by demand-based scaling of resources.  ...  As CPU utilization is one of crucial metrics for evaluating the cloud data center server's performance and is used by researchers for estimating server's future performance [20] - [22] , thus we predict  ... 
doi:10.1109/access.2020.2966678 fatcat:n7qc6lh4tvdl3bm3rkafoukca4
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