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Experimental Analysis on Autonomic Strategies for Cloud Elasticity

Simon Dupont, Jonathan Lejeune, Frederico Alvares, Thomas Ledoux
2015 2015 International Conference on Cloud and Autonomic Computing  
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

Khaled Khebbeb, Nabil Hameurlain, Faiza Belala, Hamza Sahli
2019 IET Software  
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

K. Hemapriya, J. DeeX K. Hemapriya, J. Deepa, S. Kaviarasan
2015 International Journal of Innovative Research in Science, Engineering and Technology  
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]

Carlos Mera-Gómez, Francisco Ramírez, Rami Bahsoon, Rajkumar Buyya
2017 arXiv   pre-print
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

Mostafa Ghobaei-Arani, Alireza Souri, Thar Baker, Aseel Hussien
2019 IEEE Access  
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

Muhammad Azeem Akbar, Tooba Tehreem, Shaukat Hayat, Nasrullah, Muhammad Mateen
2020 International Journal of Computing and Digital Systems  
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]

Rajkumar Buyya, Rodrigo N. Calheiros, Xiaorong Li
2012 arXiv   pre-print
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]

Javier Diaz-Montes, Ivan Rodero, Mengsong Zou, Manish Parashar
2014 Cloud Computing for Data-Intensive Applications  
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

Francisco Cruz, Francisco Maia, Miguel Matos, Rui Oliveira, João Paulo, José Pereira, Ricardo Vilaça
2013 Proceedings of the 8th ACM European Conference on Computer Systems - EuroSys '13  
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

Ali Yadavar Nikravesh, Samuel A. Ajila, Chung-Horng Lung
2017 Journal of Cloud Computing: Advances, Systems and Applications  
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

V Maruthi, P Shanthi, A Umamakeswari
2018 International Journal of Engineering & Technology  
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] • • ✓ • An Analysis of Resilience of a Cloud Based Incident Notification Process[21] • • • ✓  ... 
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  
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]

Sorin Grigorescu, Tiberiu Cocias, Bogdan Trasnea, Andrea Margheri, Federico Lombardi, Leonardo Aniello
2020 Sensors   pre-print
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]

Olena Skarlat, Philipp Hoenisch, Schahram Dustdar
2016 Lecture Notes in Business Information Processing  
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

Wei Ai, Kenli Li, Shenglin Lan, Fan Zhang, Jing Mei, Keqin Li, Rajkumar Buyya
2016 Scientific Programming  
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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