An Extension of Job-Worker Assignment Algorithm for Dynamic Job Migration for User-PC Computing System
Authors: 
Ariel Elie Asserehou Kamoyedji, Nobuo Funabiki, Hein Htet, Xudong Zhou, Minoru Kuribayashi, Shinji SugawaraAuthors Info & Claims
Ariel Elie Asserehou Kamoyedji, Nobuo Funabiki, Hein Htet, Xudong Zhou, Minoru Kuribayashi, Shinji SugawaraAuthors Info & ClaimsPages 175 - 183
Abstract
The User-PC computing system (UPC) is a very low cost master-worker model-based distributed computing platform that aims at leveraging idling personal computers (PCs) resources of a group members. In order to do so, the UPC master receives jobs from users and assigns them to available worker PCs, where they are executed using Docker. We have previously devised and implemented an efficient job-worker assignment algorithm considering CPU core utilization, for the UPC system. The latter finds an optimal assignment that minimizes the makespan in the UPC system. In this paper, we extend this algorithm to fully utilize all workers processing power and further reduce the makespan. The proposed method carefully preempts and migrates jobs from their currently assigned worker to another one, based on specific criteria. For evaluation, we conducted experiments using six worker PCs and up to 72 jobs. The extended algorithm could reduce the makespan by up to 65% compared to other existing job scheduling algorithms.
References
[1]
H. Htet, N. Funabiki, A. Kamoyedji, and M. Kuribayashi, “Design and implementation of improved user-PC computing system,” IEICE Tech. Report, NS2020-28, vol. 120, no. 69, pp. 37-42, Jun. 2020.
[2]
A. Mouat, Using Docker: developing and deploying software with containers, O'Reilly Media, Inc., Dec. 2015.
[3]
A. Kamoyedji, N. Funabiki, H. Htet and M. Kuribayashi, “A proposal of dynamic job scheduling algorithm considering CPU core utilization for User-PC computing System,” in Proc. Int. Symp. Comput. Netw. Works. (CANDARW), pp. 268-271, Nov. 2021.
[4]
Z. Pooranian, M. Shojafar, J. Abawajy, M. Singhal, “GLOA: a new job scheduling algorithm for grid computing,” Int. J. Artif. Intell. Interact. Multimed., vol. 2, no. 1, pp. 59-64, Mar. 2013.
[5]
Y. I. Seol and Y. K. Kim, “Applying dynamic priority scheduling scheme to static systems of pinwheel task model in power-aware scheduling,” Sci. World J., pp. 1-9, Jan. 2014.
[6]
R. Garg, A. Singh, “Adaptive workflow scheduling in grid computing based on dynamic resource availability,” Int. J. Eng. Sci. Tech., vol. 18, no. 2, pp. 256-269, Jun. 2015.
[7]
M. Nasri and G. Fohler, “Non-work-conserving non-preemptive scheduling: motivations, challenges, and potential solutions,” Euromicro Conf. Real-Time Sys. (ECRTS), pp. 165-175, Jul. 2016.
[8]
M. Nasri and B. B. Brandenburg, “An exact and sustainable analysis of non-preemptive scheduling,” in Proc. Real-Time Sys. Symp. (RTSS), pp. 12-23, Dec. 2017.
[9]
G. Amalarathinam and A. M. Josphin, “Dual objective dynamic scheduling algorithm (DoDySA) for heterogeneous environments,” Int. J. Advan. Comput. Sci. Tech. (ACST), vol. 10, no. 2, pp. 171-183, 2017.
[10]
M.K. Bhatia, “Task scheduling in grid computing: a review,” Int. J. Advan. Comput. Sci. Tech.(ACST), vol. 10, no. 6, pp. 1707-1714, 2017.
[11]
L. Xu, J. Qiao, S. Lin and W. Zhang, “Dynamic task scheduling algorithm with deadline constraint in heterogeneous volunteer computing platforms,” Future Internet, vol. 11, no. 6, p. 121, Jun. 2019.
[12]
G. Lucarelli, B. Moseley, N. Kim Thang, A. Srivastav and D. Trystram, “Online non-preemptive scheduling on unrelated machines with rejections,” in Proc. Symp. Paral. Algo. Archi. (SPAA), pp. 291-300, Jul. 2018.
[13]
S. Bansal, C. Hota, ”Efficient refinery scheduling Hhuristic in heterogeneous computing systems,” J. Adv. Inf. Technol., vol. 2, no. 3, pp. 159-164, Aug. 2011.
[14]
M. B. Gawali, S. K. Shinde, ”Standard deviation based modified Cuckoo optimization algorithm for task scheduling to efficient resource allocation in cloud computing,” J. Adv. Inf. Technol., vol. 8, no. 4, pp. 210-218, Nov. 2017.
[15]
H. Htet, N. Funabiki, A. Kamoyedji, M. Kuribayashi, F. Akhter, and W.-C. Kao, “An implementation of user-PC computing system using Docker container,” Int. J. Future Comput. Commun. (IJFCC), vol. 9, no. 4, pp. 66-73, Dec. 2020.
[16]
D. Herron, Node.js web development, 5th Ed., Packt Pub., Jul. 2020.
[17]
SFTP, https://www.ssh.com/ssh/sftp, (Accessed 13 Apr., 2022).
[18]
A. Ratan, E. Chou, P. Kathiravelu, and M. O. Faruque Sarker, Python network programming: conquer all your networking challenges with the powerful python language, Packt Pub., Jan. 2019.
[19]
B. Schwartz, P. Zaitsev, and V. Tkachenko, High performance MySQL: optimization, backups, and replication, 3rd Ed., O'Reilly Media, Mar. 2012.
[20]
R. McKendrick, Monitoring Docker, Packt Pub., Dec. 2015.
[21]
G. Rodola, “Efficient I/O with zero-copy & psutil,” https://gmpy. dev/static/efficient-io-with-zerocopy-syscalls.pdf, (Accessed 13 Apr., 2022).
[22]
H. Htet, N. Funabiki, A. Kamoyedji, X. Zhou, and M. Kuribayashi, “An implementation of job migration function using CRIU and Podman in Docker-based user-PC computing system,” in Proc. Int. Conf. Com. Commun. Manag. (ICCCM), pp. 92-97, Jul. 2021.
[23]
CRIU, https://www.criu.org/Main Page, (Accessed 13 Apr., 2022).
[24]
A. Kamoyedji, N. Funabiki, H. Htet and M. Kuribayashi, “A proposal of static job scheduling algorithm considering CPU core utilization for User-PC computing system,” Int. Conf. Info. Edu. Tech. (ICIET), pp. 374-379, Mar. 2021.
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- An Extension of Job-Worker Assignment Algorithm for Dynamic Job Migration for User-PC Computing System
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Published In
July 2022
289 pages
ISBN:9781450396349
DOI:10.1145/3556223
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Published: 16 October 2022
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ICCCM 2022: The 10th International Conference on Computer and Communications Management
July 29 - 31, 2022
Okayama, Japan
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