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Cloud computing based bushfire prediction for cyber–physical emergency applications

Saurabh Garg, Jagannath Aryal, Hao Wang, Tejal Shah, Gabor Kecskemeti, Rajiv Ranjan
2018 Future generations computer systems  
The evaluation results show that our Cloud based bushfire prediction system can scale resources and meet user requirements.  ...  Most of these prediction/mapping tools and models were designed to run either on a single local machine or a High performance cluster, neither of which can scale with users' needs.  ...  Tuan Do for his assistance in spatial data processing. We would also like to thank Joanne Allison for proof reading the manuscript.  ... 
doi:10.1016/j.future.2017.02.009 fatcat:pxfhgxxaubdmfnnzkthjs2rb5y

Evaluating Auto-scaling Strategies for Cloud Computing Environments

Marco A.S. Netto, Carlos Cardonha, Renato L.F. Cunha, Marcos D. Assuncao
2014 2014 IEEE 22nd International Symposium on Modelling, Analysis & Simulation of Computer and Telecommunication Systems  
Auto-scaling strategies that are not properly configured according to user workload characteristics may lead to unacceptable QoS and large resource waste.  ...  Auto-scaling is a key feature in clouds responsible for adjusting the number of available resources to meet service demand.  ...  However, we remark that the advantage of Fixed over Active in Workloads 3 and 4 is virtually negligible.  ... 
doi:10.1109/mascots.2014.32 dblp:conf/mascots/NettoCCA14 fatcat:fmqs6oi3mzdkrkmptkda556mdi

Scaling up genome annotation using MAKER and work queue

Andrew Thrasher, Zachary Musgrave, Brian Kachmarck, Douglas Thain, Scott Emrich
2014 International Journal of Bioinformatics Research and Applications  
Our framework enables it to now run without MPI while utilising a wide variety of distributed computing resources.  ...  Because of the overall increasing demand and the inherent parallelism available in many required analyses, these bioinformatics applications should ideally run on clusters, clouds and/or grids.  ...  Acknowledgements This work was supported in part by National Institutes of Health/National Institute for Allergy and Infectious Diseases grant number HHSN272200900039C and National Science Foundation grant  ... 
doi:10.1504/ijbra.2014.062994 pmid:24989862 fatcat:qfg3p2zukjannb7rxecfijm7mq

DISSECT-CF: A simulator to foster energy-aware scheduling in infrastructure clouds

Gabor Kecskemeti
2015 Simulation modelling practice and theory  
In response to the requirements of such scenarios, the new simulator introduces concepts such as: a unified model for resource sharing and a new energy metering framework with hierarchical and indirect  ...  Infrastructure as a service (IaaS) systems offer on demand virtual infrastructures so reliably and flexibly that users expect a high service level.  ...  Acknowledgements This work was partially supported by European Union's Horizon 2020 research and innovation programme under grant agreement No 644179 (ENTICE) as well as by the COST Program Action IC1305  ... 
doi:10.1016/j.simpat.2015.05.009 fatcat:z5j7xzcr5fghdgze7hra7wkklu

Machine Learning-based Orchestration of Containers: A Taxonomy and Future Directions [article]

Zhiheng Zhong, Minxian Xu, Maria Alejandra Rodriguez, Chengzhong Xu, Rajkumar Buyya
2021 arXiv   pre-print
Containerization is a lightweight application virtualization technology, providing high environmental consistency, operating system distribution portability, and resource isolation.  ...  Machine learning algorithms are accordingly employed by container orchestration systems for behavior modelling and prediction of multi-dimensional performance metrics.  ...  status of machine learning-based container orchestration researches in such fast-evolving and challenging scenarios.  ... 
arXiv:2106.12739v1 fatcat:bewvimekavduba4ku4stq32sny

Is your cloud elastic enough?

Paul C. Brebner
2012 Proceedings of the third joint WOSP/SIPEW international conference on Performance Engineering - ICPE '12  
Elasticity, the ability to rapidly scale resources up and down on demand, is an essential feature of public cloud platforms.  ...  The model is also able to predict the elasticity requirements (in terms of the maximum instance spin-up time) for the three applications. We conclude with an analysis of the results.  ...  data onto the new virtual machine, start the application, and include the new instance in a load balancer so it can be accessed externally (e.g. the Amazon Elastic Load Balancer).  ... 
doi:10.1145/2188286.2188334 dblp:conf/wosp/Brebner12 fatcat:ppw7f5m5irgrpp6jweoye4svni

Adaptive Resource Provisioning for Virtualized Servers Using Kalman Filters

Evangelia Kalyvianaki, Themistoklis Charalambous, Steven Hand
2014 ACM Transactions on Autonomous and Adaptive Systems  
This work presents a new resource management scheme that incorporates the Kalman filter into feedback controllers to dynamically allocate CPU resources to virtual machines hosting server applications.  ...  Resource management of virtualized servers in data-centres has become a critical task, since it enables costeffective consolidation of server applications.  ...  Simple time-series analysis techniques have also been used to predict future resource demands in modern virtualized shared clusters.  ... 
doi:10.1145/2626290 fatcat:2jxlqu6porcinpp73ztgolpj64

RECAP Data Acquisition and Analytics Methodology [chapter]

Paolo Casari, Jörg Domaschka, Rafael García Leiva, Thang Le Duc, Mark Leznik, Linus Närvä
2020 The Cloud-to-Thing Continuum  
The collection, analysis, and processing of infrastructure information and telemetry data lie at the very heart of RECAP.  ...  This chapter describes the infrastructure for the acquisition and processing of data from applications and systems, and explains the methodology used to derive  ...  The AR part relies Machine-Learning-based Models In order to facilitate fast online workload predictions in RECAP, we consider the Online Sequential Extreme Learning Machine (OS-ELM), which enables the  ... 
doi:10.1007/978-3-030-39863-7_2 fatcat:jwxrpjfz7jhh7amul2zv23a6iy

Network and server resource management strategies for data centre infrastructures: A survey

Fung Po Tso, Simon Jouet, Dimitrios P. Pezaros
2016 Computer Networks  
We highlight the need for and benefits of adaptive resource provisioning that alleviates reliance on static utilisation prediction models and exploits direct measurement of resource utilisation on servers  ...  The advent of virtualisation and the increasing demand for outsourced, elastic compute charged on a payas-you-use basis has stimulated the development of large-scale Cloud Data Centres (DCs) housing tens  ...  Acknowledgements The work has been supported in part by the UK Engineering and Physical Sciences Research Council (EPSRC) grants EP/N033957/1 , EP/L026015/1 , and EP/L005255/1 .  ... 
doi:10.1016/j.comnet.2016.07.002 fatcat:gcvbvxczprb2lpx4jkl2hpb5hq

Survey of Memory Management Techniques for HPC and Cloud Computing

Anna Pupykina, Giovanni Agosta
2019 IEEE Access  
In this survey, challenges of memory management in HPC and Cloud Computing, different memory management systems and optimisation techniques to increase memory utilisation are discussed in detail.  ...  However, for this scenario to succeed in practice, resources, including memory, need to be allocated with a vision that includes both the application requirements and the current and future state of the  ...  For Cloud Computing, instead, analysis and prediction of the workload or resource utilisation are typical.  ... 
doi:10.1109/access.2019.2954169 fatcat:hwtpltrdrffqdjdofhr3shjkla

Economic impact of energy saving techniques in cloud server

Bilal Ahmad, Zaib Maroof, Sally McClean, Darryl Charles, Gerard Parr
2019 Cluster Computing  
., service level agreement, virtual machine selection techniques, optimization policies, workload types etc.  ...  Cloud Computing companies (Google, Yahoo, Gaikai, ONLIVE, Amazon and eBay) use large data centers which are comprised of virtual computers that are placed globally and require a lot of power cost to maintain  ...  reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s10586-019-02946-w fatcat:agscsbs3uzajhles34yv3f4o4m

A Holistic Model of the Performance and the Energy-Efficiency of Hypervisors in an HPC Environment [chapter]

Mateusz Guzek, Sébastien Varrette, Valentin Plugaru, Johnatan E. Pecero, Pascal Bouvry
2013 Lecture Notes in Computer Science  
The efficient utilization of virtualized servers and/or computing resources requires understanding of the overheads in energy consumption and the throughput, especially on high-demanding High Performance  ...  The proposed holistic model of machine power takes into account the impact of utilisation metrics of the machine's components, as well as the employed application, virtualization, and hardware.  ...  Guzek acknowledges the support of the FNR in Luxembourg and Tri-ICT, with the AFR contract no. 1315254.  ... 
doi:10.1007/978-3-642-40517-4_13 fatcat:ilwfdhj22zdenj5wxpzex3vzbm

Artificial Intelligence (AI)-Centric Management of Resources in Modern Distributed Computing Systems [article]

Shashikant Ilager, Rajeev Muralidhar, Rajkumar Buyya
2020 arXiv   pre-print
Contemporary Distributed Computing Systems (DCS) such as Cloud Data Centres are large scale, complex, heterogeneous, and distributed across multiple networks and geographical boundaries.  ...  In this regard, this paper aims to draw the motivations and necessities for data-driven solutions in resource management.  ...  Generating the Large-scale Data Sets Machine learning models require large amounts of training data for improved accuracy.  ... 
arXiv:2006.05075v2 fatcat:tck54mz4yff3deesetflj34wke

Elastic Scaling of e-Infrastructures to Support Data-Intensive Research Collaborations

Marcos Nino-Ruiz, Christopher Bayliss, Gerson Galang, Guido Grazioli, Rosana Rabanal, Martin Tomko, Richard O. Sinnott
2014 2014 IEEE 10th International Conference on e-Science  
For many research endeavours, e-Infrastructures need to provide predictable, on-demand access to large-scale computational resources with high data availability.  ...  Abstract-For many research endeavours, e-Infrastructures need to provide predictable, on-demand access to large-scale computational resources with high data availability.  ...  information on virtual machine resources.  ... 
doi:10.1109/escience.2014.13 dblp:conf/eScience/Nino-RuizBGGRTS14 fatcat:qxvje4ipy5bafkdzbpbmafe4zq

Extending the Cutting Stock Problem for Consolidating Services with Stochastic Workloads

Markus Haehnel, John Martinovic, Guntram Scheithauer, Andreas Fischer, Alexander Schill, Waltenegus Dargie
2018 IEEE Transactions on Parallel and Distributed Systems  
The workloads of these benchmarks have been generated based on the CPU utilisation traces of 100 real-world virtual machines which we obtained from a Google data centre hosting more than 32000 virtual  ...  The effect of these conditions can be minimised by attempting to balance the demand for and the supply of resources through a careful prediction of future workloads and their efficient consolidation.  ...  ACKNOWLEDGMENTS This work has been partially funded by the German Research Foundation (DFG) in the Collaborative Research Center 912 "Highly Adaptive Energy-efficient Computing" (HAEC).  ... 
doi:10.1109/tpds.2018.2819680 fatcat:u6uzoqc5azdvzm2q24oteseeru
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