The development of the system for arc nordugrid based grid-computing organization using virtual environments of the docker platform
Keywords:grid, cloud computing, virtualization, task scheduling, replication
The study of modern frameworks and means of using virtualization in a grid environment confirmed the relevance of the task of automated configuration of the environment for performing tasks in a grid environment.
Setting up a task execution environment using virtualization requires the implementation of appropriate algorithms for scheduling tasks and distributed storage of images of virtual environments in a grid environment. Existing cloud infrastructure solutions to optimize the process of deploying virtual machines on computing resources do not have integration with the Arc Nordugrid middleware, which is widely used in grid infrastructures. An urgent task is to develop tools for scheduling tasks and placing images of virtual machines on the resources of the grid environment, taking into account the use of virtualization tools.
The results of the implementation of services of the framework are presented that allow to design and perform computational tasks in a grid environment based on ARC Nordugrid using the virtual environment of the Docker platform. The presented results of the implementation of services for scheduling tasks in a grid environment using a virtual computing environment are based on the use of a scheduling algorithm based on the dynamic programming method.
Evaluations of the effectiveness of the solutions developed on the basis of a complex of simulation models showed that the use of the proposed algorithm for scheduling and replicating virtual images in a grid environment can reduce the execution time of a computational task by 88 %. Such estimates need further refinement; it is predicted that planning efficiency will increase over time with an increase in the number of running tasks due to the redistribution of the storage of virtual images
Di Meglio, A., Riedel, M., Memon, S. M., Loomis, C., Salomoni, D. (2011). Grids and Clouds Integration and Interoperability: an overview. Proceedings of The International Symposium on Grids and Clouds and the Open Grid Forum – PoS(ISGC 2011 & OGF 31). doi: https://doi.org/10.22323/1.133.0112
Foster, I. (2002). What is the Grid? A Three Point Checklist. GRIDToday. Available at: https://www.mcs.anl.gov/~itf/Articles/WhatIsTheGrid.pdf
Mell, P. M., Grance, T. (2011). The NIST Definition of Cloud Computing. Recommendations of the National Institute of Standards and Technology. NIST. doi: https://doi.org/10.6028/nist.sp.800-145
ARC. NorduGrid. Available at: http://www.nordugrid.org/
Krašovec, B., Filipčič, A. (2019). Enhancing the Grid with Cloud Computing. Journal of Grid Computing, 17 (1), 119–135. doi: https://doi.org/10.1007/s10723-018-09472-w
Pogorilyy, S. D., Boyko, Y., Salnikov, A. O., Sliusar, Ie. A., Boretsky, O. (2017). Images of virtual machines running as grid tasks provisional configuration and formation. Naukovi pratsi Donetskoho natsionalnoho tekhnichnoho universytetu. Seriya: Informatyka, kibernetyka ta obchysliuvalna tekhnika, 2, 90–97. Available at: http://nbuv.gov.ua/UJRN/Npdntu_inf_2017_2_14
Haug, S., Sciacca, F. G. (2017). ATLAS computing on Swiss Cloud SWITCHengines. Journal of Physics: Conference Series, 898, 052017. doi: https://doi.org/10.1088/1742-6596/898/5/052017
ATLAS Experiment. Available at: https://atlas.cern/
Keahey, K., Riteau, P., Anderson, J., Zhen, Z. (2019). Managing Allocatable Resources. 2019 IEEE 12th International Conference on Cloud Computing (CLOUD). doi: https://doi.org/10.1109/cloud.2019.00019
Donyagard Vahed, N., Ghobaei-Arani, M., Souri, A. (2019). Multiobjective virtual machine placement mechanisms using nature-inspired metaheuristic algorithms in cloud environments: A comprehensive review. International Journal of Communication Systems, 32 (14), e4068. doi: https://doi.org/10.1002/dac.4068
Mohammad, S. G. (2019). A dynamic replication mechanism in data grid based on a weighted priority - based scheme. i-Manager’s Journal on Cloud Computing, 6 (1), 9. doi: https://doi.org/10.26634/jcc.6.1.15897
Chang, Y., Gu, C., Luo, F. (2016). A novel energy-aware and resource efficient virtual resource allocation strategy in IaaS cloud. 2016 2nd IEEE International Conference on Computer and Communications (ICCC). doi: https://doi.org/10.1109/compcomm.2016.7924911
Ashraf, A., Porres, I. (2017). Multi-objective dynamic virtual machine consolidation in the cloud using ant colony system. International Journal of Parallel, Emergent and Distributed Systems, 33 (1), 103–120. doi: https://doi.org/10.1080/17445760.2017.1278601
Kazymyr, V., Prila, O., Kryshchenko, M. (2017). The use of dynamic virtual images in a grid environment with replication support. Technical Sciences and Technology, 3 (9), 88–97. doi: https://doi.org/10.25140/2411-5363-2017-3(9)-88-97
Prila, O., Kazymyr, V., Kryshchenko, M., Sysa, D. (2018). The technology of reliable task execution in grid environment using dynamic virtual images. 2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT). doi: https://doi.org/10.1109/dessert.2018.8409109
Apache NetBeans. Available at: https://netbeans.apache.org/
Git. Available at: https://git-scm.com/
Maven. Welcome to Apache Maven. Available at: https://maven.apache.org/
GridSim. Available at: https://swmath.org/software/1392
Prila, O. A. (2013). The algorithm of job scheduling in Grid environment based on the dynamic programming method. Visnyk Chernihivskoho derzhavnoho tekhnolohichnoho universytetu. Seriya: Tekhnichni nauky, 4 (69), 153–162.
Prila, O. (2013). Framework for grid application development with support of different types of large-scale computing tasks. Eastern-European Journal of Enterprise Technologies, 4 (2 (64), 8–14. Available at: http://journals.uran.ua/eejet/article/view/16598
About Registry. Available at: https://docs.docker.com/registry/introduction/
How to Cite
Copyright (c) 2021 Olga Prila, Volodymyr Kazymyr, Volodymyr Bazylevych, Oleksandr Sysa
This work is licensed under a Creative Commons Attribution 4.0 International License.
The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.