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Experimental Analysis on Autonomic Strategies for Cloud Elasticity
2015
2015 International Conference on Cloud and Autonomic Computing
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We present an experimental analysis of a sub-set of those elasticity tactics under different scenarios in order to provide insights on strategies that could drive the autonomic selection of the proper ...
Then, we describe how our autonomic cloud elasticity model relies on dynamic selection of elasticity tactics. ...
Elasticity Strategies for Autonomic Cloud Services In this section, we describe our autonomic cloud elasticity model which relies on dynamic selection of elasticity strategies.
A. ...
doi:10.1109/iccac.2015.22
dblp:conf/iccac/DupontLOL15
fatcat:rvvv5elqijhwzkoxuietk5qwgi
Formal modelling and verifying elasticity strategies in cloud systems
2019
IET Software
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They introduce elasticity strategies to describe cloud systems' auto-adaptation behaviours. ...
One step further, they encode the bigraphical specifications into Maude language to enable an autonomic executability of the elastic behaviours and verify their correctness. ...
Another contribution of this study consists of providing an experimental analysis of cloud systems' elasticity strategies based on a queuing approach. ...
doi:10.1049/iet-sen.2018.5030
fatcat:kyjeueab5nc3fosinl42byu23y
Optimized Data Center in IaaS Using Cloud Computing Systems
english
2015
International Journal of Innovative Research in Science, Engineering and Technology
english
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Future works will include the analysis of autonomic techniques able to change on-thefly the system configuration in order to react to a change on the working conditions. ...
and cloud-specific strategies. ...
An experimental evaluation in Amazon Elastic Compute Cloud (EC2) verified this approach.
III. ...
doi:10.15680/ijirset.2015.0405043
fatcat:ijhhrxbokncfrpv5bn2hux5rw4
A Debt-Aware Learning Approach for Resource Adaptations in Cloud Elasticity Management
[article]
2017
arXiv
pre-print
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To address this limitation, we propose a technical debt-aware learning approach for autonomous elasticity management based on a reinforcement learning of elasticity debts in resource provisioning; the ...
Elasticity is a cloud property that enables applications and its execution systems to dynamically acquire and release shared computational resources on demand. ...
ACKNOWLEDGMENT We thank Tao Chen for his helpful comments on the paper. ...
arXiv:1702.07431v1
fatcat:d3fbejh2qzf3hmm2buwdc2shdm
ControCity: An Autonomous Approach for Controlling Elasticity Using Buffer Management in Cloud Computing Environment
2019
IEEE Access
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Cloud computing has been one of the most popular distributed computing paradigms. Elasticity is a crucial feature that distinguishes cloud computing from other distributed computing models. ...
Buffer manager controls the queue of requests, and elasticity manager of the middleware layer using the learning automata provides a solution for controlling the elasticity of the cloud platform. ...
[20] have presented an autonomic decentralized elasticity controller for managing resources on web applications in cloud environments. ...
doi:10.1109/access.2019.2932462
fatcat:2vcocrhhmbdbfjdm25epwsyftm
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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During runtime, autonomic resource provisioning is not an easy task to choose the accurate amount of resources for service-based cloud applications. ...
For this reason, it is required to guess the future demands for self-adaptive resources to deal with the irregular requests based on runtime workload changes of service-based cloud applications. ...
In [6] researchers presented that fuzzy logic can progress the scheduling strategy of process and response time for cloud-based applications. ...
doi:10.12785/ijcds/090301
fatcat:ly2sd6rbkbewvljg5eeypek5bm
Autonomic Cloud Computing: Open Challenges and Architectural Elements
[article]
2012
arXiv
pre-print
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2012 2012 Third International Conference on Emerging Applications of Information Technology unpublished doi:10.1109/eait.2012.6407847 fatcat:7jfdt46idnfpldt7qii5dsswea
In this direction, this paper identifies open issues in autonomic resource provisioning and presents innovative management techniques for supporting SaaS applications hosted on Clouds. ...
They need automated and integrated intelligent strategies for provisioning of resources to offer services that are secure, reliable, and cost-efficient. ...
We thank Deepak Poola and Nikolay Grozev for their comments on improving the paper. ...
arXiv:1209.3356v1
fatcat:mz5w7lvhbzb3rof6w2psls5fcq
Federating Advanced Cyberinfrastructures with Autonomic Capabilities
[chapter]
2014
Cloud Computing for Data-Intensive Applications
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Clouds provide on-demand access to computing utilities, an abstraction of unlimited computing resources, and support for ondemand scale up, scale down and scale out. ...
We demonstrate the effectiveness of the proposed framework and autonomic mechanisms through the discussion of an experimental evaluation of illustrative use case application scenarios, and from these experiences ...
We experimentally investigated, from an application's perspective, possible usage modes for integrating HPC and clouds as well as how autonomic computing can support these modes. ...
doi:10.1007/978-1-4939-1905-5_9
fatcat:eyuo5q37enaofehsubefabd7ky
MeT
2013
Proceedings of the 8th ACM European Conference on Computer Systems - EuroSys '13
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MET is a prototype for a Cloud-enabled framework that can be used alone or in conjunction with OpenStack for the automatic and heterogeneous reconfiguration of a HBase deployment. ...
Next, we go beyond current state of the art elastic systems limited to uninformed replica addition and removal by: i) reconfiguring existing replicas according to access patterns and ii) adding replicas ...
Valério de Carvalho for his valuable insights on bin-packing problems. ...
doi:10.1145/2465351.2465370
dblp:conf/eurosys/CruzMMOPPV13
fatcat:mpostam25rc6pc7vvfed52jvfq
An autonomic prediction suite for cloud resource provisioning
2017
Journal of Cloud Computing: Advances, Systems and Applications
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Prediction techniques have been proposed for cloud computing to improve cloud resource management. ...
Based on the theoretical and the experimental results, this paper designs a self-adaptive prediction suite. ...
AYN designed and implemented the experiments based on guidance from SAA and CL. All authors read and approved the final manuscript. ...
doi:10.1186/s13677-017-0073-4
fatcat:7i77bjt22nfdfd6fj3fsltrhna
Enhanced Adaptive Learning Mechanism for Cloud Selection
2018
International Journal of Engineering & Technology
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Experimental results proved that using this new strategy, best cloud selection is made efficiently. ...
This paper studies the cloud selection and proposed a way to improve the cloud selection based on related measures. ...
analyze elasticity enablers of cloud services[20]
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An Analysis of Resilience of a Cloud Based Incident Notification
Process[21]
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✓ ...
doi:10.14419/ijet.v7i2.24.12149
fatcat:jvgrv6omdjcy5j3pll5nc3d2vq
Adaptive Resource Management and Provisioning in the Cloud Computing: A Survey of Definitions, Standards and Research Roadmaps
2017
KSII Transactions on Internet and Information Systems
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A solution is proposed for autonomic resource management in the federated clouds, using machine learning and statistical analysis in order to provide better and efficient resource management. ...
This study reviews the current challenges and open issues in cloud computing, with the focus on autonomic resource management especially in federated clouds. ...
In this way, cost decreases for both customers and cloud providers, since customers pay costs based on usage. Self-management is vital for autonomic system. ...
doi:10.3837/tiis.2017.09.006
fatcat:a7cyj63deveqfnchzdixn5g54e
Cloud2Edge Elastic AI Framework for Prototyping and Deployment of AI Inference Engines in Autonomous Vehicles
[article]
2020
Sensors
pre-print
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This paper proposes a novel framework for developing so-called AI Inference Engines for autonomous driving applications based on deep learning modules, where training tasks are deployed elastically over ...
Based on our proposed data driven V-Model, we introduce a simple yet elegant solution for the AI components development cycle, where prototyping takes place in the cloud according to the Software-in-the-Loop ...
Different DNN models are suggested based on this analysis. ...
doi:10.3390/s20195450
pmid:32977409
pmcid:PMC7582930
arXiv:2009.11722v1
fatcat:t4zglrnltfdmjnxlemaxwmsjqq
On Energy Efficiency of BPM Enactment in the Cloud
[chapter]
2016
Lecture Notes in Business Information Processing
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This paper is focused on the fulfillment of the principles of Green Computing and Green Business Process Management on the basis of Cloud Elasticity to support Elastic Processes. ...
Recently, Cloud Elasticity has been utilized for Business Process Enactment in the Cloud as the involved services face highly volatile demand levels. ...
The migration strategy is based on accounting for energy probes, i.e. actual energy measurements. ...
doi:10.1007/978-3-319-42887-1_39
fatcat:wfolinfgwffwtmspeblvlt2xzq
On Elasticity Measurement in Cloud Computing
2016
Scientific Programming
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Furthermore, our simulation and experimental results validate that the proposed measurement approach is not only correct but also robust and is effective in computing and comparing the elasticity of cloud ...
Existing work on elasticity lack of solid and technical way of defining elasticity measurement and definitions of elasticity metrics have not been accurate enough to capture the essence of elasticity measurement ...
Such a hot standby strategy increases cloud elasticity by reducing u . . . . Relevant Properties of Clouds. ...
doi:10.1155/2016/7519507
fatcat:cdihyoyubjfvpgjnsvgvuurwfi
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