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A Comparison of Reinforcement Learning Techniques for Fuzzy Cloud Auto-Scaling
2017
2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)
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A self-adaptive fuzzy logic controller is combined with two reinforcement learning (RL) approaches: (i) Fuzzy SARSA learning (FSL) and (ii) Fuzzy Q-learning (FQL). ...
A goal of cloud service management is to design self-adaptable auto-scaler to react to workload fluctuations and changing the resources assigned. ...
[6] investigate horizontal auto-scaling using threshold-based and reinforcement learning techniques. ...
doi:10.1109/ccgrid.2017.15
dblp:conf/ccgrid/ArabnejadPJE17
fatcat:nh2rs5xknncxllwbtxh2xkge5q
Fuzzy Self-Learning Controllers for Elasticity Management in Dynamic Cloud Architectures
2016
2016 12th International ACM SIGSOFT Conference on Quality of Software Architectures (QoSA)
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The experimental results demonstrate that FQL4KE outperforms both a fuzzy controller without learning and the native Azure auto-scaling. ...
We introduce FQL4KE, a self-learning fuzzy controller that learns and modifies fuzzy rules at runtime. ...
Fuzzy Q-Learning Until this stage, we have shown how to design a fuzzy controller for auto-scaling a cloud-based application where the elasticity policies are provided by users at design-time, like RobusT2Scale ...
doi:10.1109/qosa.2016.13
dblp:conf/qosa/JamshidiSPAME16
fatcat:uj5w3r7pfrcmvovk57kbccuczm
Self-Learning Cloud Controllers: Fuzzy Q-Learning for Knowledge Evolution
[article]
2015
arXiv
pre-print
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The experimental results indicate that FQL4KE outperforms our previously developed fuzzy controller without learning mechanisms and the native Azure auto-scaling. ...
In this paper, we propose learning adaptation rules during runtime. To this end, we introduce FQL4KE, a self-learning fuzzy cloud controller. ...
ACKNOWLEDGMENT The authors would like to thank Soodeh Farokhi and Saeid Masoumzadeh for their constructive comments on the final draft of the paper. ...
arXiv:1507.00567v1
fatcat:uyci4bfkwbbuzgypzzi63pqajy
Uncertainty Aware Resource Provisioning Framework for Cloud Using Expected 3-SARSA Learning Agent: NSS and FNSS Based Approach
2019
Cybernetics and Information Technologies
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The performance of the proposed work compared to the existing fuzzy auto scaling work achieves the throughput of 80% with the learning rate of 75% on homogeneous and heterogeneous workloads by considering ...
Efficiently provisioning the resources in a large computing domain like cloud is challenging due to uncertainty in resource demands and computation ability of the cloud resources. ...
A comparison of fuzzy SARSA and fuzzy Q-Learning towards auto-scaling of resources in the cloud environment is given in [24] . ...
doi:10.2478/cait-2019-0028
fatcat:xnkaaf32iffofcyfjo7bw24b3u
Auto-scaling Web Applications in Clouds: A Taxonomy and Survey
[article]
2017
arXiv
pre-print
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In this paper, we comprehensively analyze the challenges that remain in auto-scaling web applications in clouds and review the developments in this field. ...
We present a taxonomy of auto-scalers according to the identified challenges and key properties. We analyze the surveyed works and map them to the taxonomy to identify the weaknesses in this field. ...
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
A Self-Adaptive Resource Provisioning Approach using Fuzzy Logic for Cloud-Based Applications
2020
International Journal of Computing and Digital Systems
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Based on fuzzy logic, cloud applications having self-learning provisioning resources outperformed the hybrid resource provisioning approach. ...
Additionally, the proposed fuzzy logic approach enhanced the performance of planning phase for better decision making. ...
ACKNOWLEDGMENT The authors declare no conflict of interest. ...
doi:10.12785/ijcds/090301
fatcat:ly2sd6rbkbewvljg5eeypek5bm
Adaptive Service Performance Control using Cooperative Fuzzy Reinforcement Learning in Virtualized Environments
2017
Proceedings of the10th International Conference on Utility and Cloud Computing - UCC '17
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To this end, we extend the standard reinforcement learning approach in two ways: a) we formulate the system state as a fuzzy space and b) exploit a set of cooperative agents to explore multiple fuzzy states ...
A popular approach is fine-grained resource provisioning via auto-scaling mechanisms that rely on either threshold-based adaptation rules or sophisticated queuing/control-theoretic models. ...
The closest technique to the proposed mechanism is Auto-scale [24] , an RL-based technique for adaptive QoS control via vertical scaling using Neuro-Fuzzy function approximations. ...
doi:10.1145/3147213.3147225
dblp:conf/ucc/IbidunmoyeMLE17
fatcat:jgrqm645cvgwncl3bnx6glztpi
Autonomic resource provisioning for cloud-based software
2014
Proceedings of the 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems - SEAMS 2014
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The state-of-thepractice with respect to auto-scaling involves specifying thresholdbased rules to implement elasticity policies for cloud-based applications. ...
This paper exploits fuzzy logic to enable qualitative specification of elasticity rules for cloud-based software. ...
Reinforcement learning (e.g., [42] ) enable learning elasticity policies from observations. However, it requires long learning, which is only applicable for stable workloads. ...
doi:10.1145/2593929.2593940
dblp:conf/icse/JamshidiAP14
fatcat:p4vpr3ahrvbnrdklfkirjhucmq
Auto-scaling techniques for elastic data stream processing
2014
Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems - DEBS '14
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In this paper we investigate the application of different auto-scaling techniques for solving this problem. ...
, and (3) we perform evaluation of the selected auto scaling techniques using the real world data. ...
REQUIREMENTS FOR AN AUTO-SCALING TECHNIQUE For selecting possible approaches from the set of available auto-scaling techniques [11] we propose a set of requirements for an auto-scaling technique in an ...
doi:10.1145/2611286.2611314
dblp:conf/debs/HeinzePJF14
fatcat:plgqlm2wore6hkh34a45ehffiq
Auto-scaling techniques for elastic data stream processing
2014
2014 IEEE 30th International Conference on Data Engineering Workshops
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In this paper we investigate the application of different auto-scaling techniques for solving this problem. ...
, and (3) we perform evaluation of the selected auto scaling techniques using the real world data. ...
REQUIREMENTS FOR AN AUTO-SCALING TECHNIQUE For selecting possible approaches from the set of available auto-scaling techniques [11] we propose a set of requirements for an auto-scaling technique in an ...
doi:10.1109/icdew.2014.6818344
dblp:conf/icde/HeinzePJF14
fatcat:zy7pzq4rbjg5fjqvsbhyuokqda
Intelligent Autoscaling of Microservices in the Cloud for Real-time Applications
2021
IEEE Access
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Advancements in machine learning and reinforcement learning (RL) provides a means for autoscaling in cloud applications with no domain knowledge. ...
What adds to the challenge is that cloud applications impose quality of service (QoS) requirements and have various resource demands requiring a customized scaling approach. ...
Our research builds on this where we use microservices log data along with machine learning and reinforcement techniques to auto scale the cloud microservices while abiding with QoS constraints. ...
doi:10.1109/access.2021.3061890
fatcat:awgamwbrffdhbchq5xuca7shja
Exterminating Computational Limits of Machine Learning with Merits of Serverless
2018
International Journal of Engineering Research and
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A serverless compute may give an optimal solution to the computational resources provided by the cloud. ...
The trend of determining patterns using the various machine-learning, data mining, deep-learning or neural networks are limited due to the computational power of machines. ...
Infra: SLO Aware Elastic Auto Scaling in the Cloud for Cost Reduction Sidhanta and Mukhopadhyay[2016] presented SLO (Service Level Objective) Aware Elastic Auto Scaling in the cloud for cost reduction. ...
doi:10.17577/ijertv7is010147
fatcat:xsbi5flvkjgtjnxctkspzggxhu
Research on Auto-Scaling of Web Applications in Cloud: Survey, Trends and Future Directions
2019
Scalable Computing : Practice and Experience
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In this article, we presented the literature survey for auto-scaling techniques of web applications in cloud computing. ...
One of the key challenges for web application in cloud computing is auto-scaling. ...
One of the rule-based technique for an auto-scaling approach is fuzzy rules. In this technique, rules are defined using if-else conditions. ...
doi:10.12694/scpe.v20i2.1537
fatcat:5zdylggvtjdslichn6mpoleese
Improved Q Network Auto-Scaling in Microservice Architecture
2022
Applied Sciences
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A cloud provider requires flexible resource management to meet the continually changing demands, such as auto-scaling and provisioning. ...
Microservice architecture has emerged as a powerful paradigm for cloud computing due to its high efficiency in infrastructure management as well as its capability of largescale user service. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app12031206
fatcat:73rul7ujb5br3dmt7irftx3t54
Applying reinforcement learning towards automating resource allocation and application scalability in the cloud
2012
Concurrency and Computation
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By applying a temporal difference reinforcement learning algorithm known as Q-learning, optimal scaling policies can be determined. ...
Additionally reinforcement learning techniques typically suffer from curse of dimensionality problems, where the state space grows exponentially with each additional state variable. ...
ACKNOWLEDGMENT The authors would like to gratefully acknowledge the continued support of Science Foundation Ireland. (2011) ...
doi:10.1002/cpe.2864
fatcat:tilsmxw6h5eyhedqe2y3si6pyy
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