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A GA based approach for solving ring design telecommunication network

Published: 19 July 2022 Publication History

Abstract

Improvement in physical network infrastructure is often required to enhance the services provided by telecommunication companies to meet consumer demand. One aspect of enhancement is to improve broadband access which is based on the Gigabit Passive Optical Network (GPON) technology for Fiber-To-The-Home (FTTH) networks. However, designing and deploying FTTH networks are costly due to the infrastructure costs such as digging up the road, laying the cables, installing the junction boxes, etc.
This paper, based on a GA approach, focuses on optimizing the cost of designing ring topology for the GPON FTTH network. Our approach consists of three steps to achieve a near-optimum solution. The first step exploits the similarity between the traveling salesman problem (TSP) and the ring design problem. A GA is used to find a TSP solution for our problem. If the solution is not valid, then a second step based on another GA is executed to find a set of valid ring designs. The third step is used to group the obtained valid solutions and apply a customized GA with a specific crossover for further improvement. The proposed method will be tested with different networks to illustrate the effectiveness of our approach for solving the ring design problems.

References

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Pereira, J., 2016. Next Generation Network (NGN)Challenges on Access Networks. New Advances in Information Systems and Technologies, pp.341--350
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Shakya, S., Poon, K. and Ouali, A., 2018. A GA based network optimization tool for passive in-building distributed antenna systems. Proceedings of the Genetic and Evolutionary Computation Conference,
[3]
Le, H.N. (2014). FTTH network optimization. Journal of Telecommunications and Information Technology. 2014. 88--99.
[4]
Puljić, K. and Manger, R., 2013. Comparison of eight evolutionary crossover operators for the vehicle routing problem. MATHEMATICAL COMMUNICATIONS Math, 18, pp.359--375.
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A. Starkey, H. Hagras, S. Shakya and G. Owusu. A many-objective genetic type- 2 fuzzy logic system for the optimal allocation of mobile field engineers, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Vancouver, BC, 2016, pp. 2051--2058
[6]
M. Pelikan and D. E. Goldberg. Hierarchical BOA solves Ising spin glasses and MAXSAT. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2003), pages 1271--1282, 2003. Also IlliGAL Report No. 2003001.
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Mazidi, Arash & Damghanijazi, Elham. (2017). Meta-Heuristic Approaches for Solving Travelling Salesman Problem. International Journal of Advanced Research in Computer Science. 5.

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  • (2024)Image Text Extraction and Natural Language Processing of Unstructured Data from Medical ReportsMachine Learning and Knowledge Extraction10.3390/make60200646:2(1361-1377)Online publication date: 18-Jun-2024

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cover image ACM Conferences
GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference Companion
July 2022
2395 pages
ISBN:9781450392686
DOI:10.1145/3520304
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publication History

Published: 19 July 2022

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Author Tags

  1. GA
  2. ring design problem
  3. travelling salesman problem

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  • (2024)Image Text Extraction and Natural Language Processing of Unstructured Data from Medical ReportsMachine Learning and Knowledge Extraction10.3390/make60200646:2(1361-1377)Online publication date: 18-Jun-2024

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