The Delay Time Profile of Multistage Networks with Synchronization

Author:

Barron Yonit1ORCID

Affiliation:

1. Industrial Engineering and Management, Ariel University, Ariel 40700, Israel

Abstract

The interaction between projects and servers has grown significantly in complexity; thus, applying parallel calculations increases dramatically. However, it should not be ignored that parallel processing gives rise to synchronization constraints and delays, generating penalty costs that may overshadow the savings obtained from parallel processing. Motivated by this trade-off, this study investigates two special and symmetric systems of split–join structures: (i) parallel structure and (ii) serial structure. In a parallel structure, the project arrives, splits into m parallel groups (subprojects), each comprising n subsequent stages, and ends after all groups are completed. In the serial structure, the project requires synchronization after each stage. Employing a numerical study, we investigates the time profile of the project by focusing on two types of delays: delay due to synchronization overhead (occurring due to the parallel structure), and delay due to overloaded servers (occurring due to the serial structure). In particular, the author studies the effect of the number of stages, the number of groups, and the utilization of the servers on the time profile and performance of the system. Further, this study shows the efficiency of lower and upper bounds for the mean sojourn time. The results show that the added time grows logarithmically with m (parallelism) and linearly with n (seriality) in both structures. However, comparing the two types of split–join structures shows that the synchronization overhead grows logarithmically undr both parallelism and seriality; this yields an unexpected duality property of the added time to the serial system.

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Reference48 articles.

1. Alesawi, S., and Ghanem, S. (2019, January 18–21). Overcome heterogeneity impact in modeled fork-join queuing networks for tail prediction. Proceedings of the 2019 International Conference on Computing, Networking and Communications (ICNC), IEEE, Honolulu, HI, USA.

2. The analysis of big data centers performance;Gorbunova;Adv. Syst. Sci. Appl.,2022

3. A black-box fork-join latency prediction model for data-intensive applications;Nguyen;IEEE Trans. Parallel Distrib. Syst.,2020

4. Ardagna, D., Bernardi, S., Gianniti, E., Karimian Aliabadi, S., Perez-Palacin, D., and Requeno, J.I. (2016, January 14–16). Modeling performance of hadoop applications: A journey from queueing networks to stochastic well formed nets. Proceedings of the Algorithms and Architectures for Parallel Processing: 16th International Conference, ICA3PP 2016, Granada, Spain. Proceedings 15.

5. Using multi-target feature evaluation to discover factors that affect business process behavior;Delias;Comput. Ind.,2018

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