Login Register Cart 0
Generic placeholder image

International Journal of Sensors, Wireless Communications and Control

Editor-in-Chief

ISSN (Print): 2210-3279
ISSN (Online): 2210-3287

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Fiber Wireless (FiWi) Access Network Planning & Deployment using Reptile Search Algorithm

Author(s): Nitin Chouhan, Uma Rathore Bhatt* and Vijay Bhat

Volume 13, Issue 1, 2023

Published on: 05 April, 2023

Page: [40 - 56] Pages: 17

DOI: 10.2174/2210327913666230316150418

Price: $65

Abstract

Aim: The aim of this study is the deployment of components in an efficient manner to make a cost-effective FiWi network.

Background: Fiber Wireless access network is the boost to broadband access technology for providing network services to Internet users at a lower cost. Deployment of components in FiWi access network is very crucial since it affects the deployment cost and network performance.

Objective: We investigate the planning process for efficient placement of components in FiWi access networks. For optimizing the position of components (wireless routers and ONUs) in the network, a novel nature inspired Reptile Search Algorithm (RSA) is proposed in the paper.

Methods: Extensive simulation is carried out to implement proposed work. A simulation model and code is developed in MATLAB to get the optimized position of components for existing and proposed algorithms.

Results: We compare the performance of proposed algorithm with existing algorithm. The obtained results show that the proposed algorithm has superior performance than the existing algorithm.

Conclusion: The present work optimizes the position of components using RSA algorithm. RSA returns the lower number of required wireless routers/ONUs, lesser TCD, increased AONUC, fast convergence rate, lesser execution run time than WSSA algorithm. The outcome of the paper highlights the importance of the proposed work in network planning and component deployment in FiWi access network.

« Previous Next »
Graphical Abstract

[1]
Liu Y, Guo L, Gong B, et al. Green survivability in Fiber-Wireless (FiWi) broadband access network. Opt Fiber Technol 2012; 18(2): 68-80.
[http://dx.doi.org/10.1016/j.yofte.2011.12.002]
[2]
Shaddad RQ, Mohammad AB, Al-Gailani SA, Al-hetar AM, Elmagzoub MA. A survey on access technologies for broadband optical and wireless networks. J Netw Comput Appl 2014; 41: 459-72.
[http://dx.doi.org/10.1016/j.jnca.2014.01.004]
[3]
Ghazisaidi N, Maier M, Assi C. Fiber-wireless (FiWi) access networks: A survey. IEEE Commun Mag 2009; 47(2): 160-7.
[http://dx.doi.org/10.1109/MCOM.2009.4785396]
[4]
Ghazisaidi N, Maier M. Fiber-wireless (FiWi) access networks: Challenges and opportunities. IEEE Netw 2011; 25(1): 36-42.
[http://dx.doi.org/10.1109/MNET.2011.5687951]
[5]
Bhatt UR, Chouhan N, Upadhyay R. Cost Efficient Algorithm for ONU Placement in Fiber-Wireless (FiWi) Access Networks. Procedia Comput Sci 2015; 46: 1303-10.
[http://dx.doi.org/10.1016/j.procs.2015.01.055]
[6]
Liu Y, Guo L, Wei X. Optimizing backup optical-network-units selection and backup fibers deployment in survivable hybrid wireless-optical broadband access networks. J Lightwave Technol 2012; 30(10): 1509-23.
[http://dx.doi.org/10.1109/JLT.2012.2188498]
[7]
Holland JH. Genetic Algorithms. Sci Am 1992; 267(1): 66-72.
[http://dx.doi.org/10.1038/scientificamerican0792-66]
[8]
Zou W, Liu T, Shi Y. Optimization of the maximum range of supercavitating vehicles based on a genetic algorithm. Ocean Eng 2021; 239: 109892.
[http://dx.doi.org/10.1016/j.oceaneng.2021.109892]
[9]
Eglese RW. Simulated annealing: A tool for operational research. Eur J Oper Res 1990; 46(3): 271-81.
[http://dx.doi.org/10.1016/0377-2217(90)90001-R]
[10]
Kennedy J, Eberhart R. Particle swarm optimization. Proceedings of ICNN'95 - International Conference on Neural Networks. 1995 27 Nov – 01 Dec; Perth, WA, Australia: IEEE. 1995.
[http://dx.doi.org/10.1109/ICNN.1995.488968]
[11]
Dorigo M, Di Caro G. Ant colony optimization: a new meta-heuristic. Proceedings of the 1999 Congress on Evolutionary Computation-CEC99. 1999 July 06-09; Washington, DC, USA: IEEE. 1999.
[http://dx.doi.org/10.1109/CEC.1999.782657]
[12]
Rao RV, Savsani VJ, Vakharia DP. Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems. Comput Aided Des 2011; 43(3): 303-15.
[http://dx.doi.org/10.1016/j.cad.2010.12.015]
[13]
Akay B, Karaboga D. A modified Artificial Bee Colony algorithm for real-parameter optimization. Inf Sci 2012; 192: 120-42.
[http://dx.doi.org/10.1016/j.ins.2010.07.015]
[14]
Gandomi AH, Yang XS, Alavi AH. Cuckoo search algorithm: A metaheuristic approach to solve structural optimization problems. Eng Comput 2013; 29(1): 17-35.
[http://dx.doi.org/10.1007/s00366-011-0241-y]
[15]
Yang XS. Firefly algorithms for multimodal optimization. Proceedings of the Stochastic Algorithms: Foundations and Applications (SAGA '09). 2009 Oct 26-28; Sapporo, Japan: Springer. 2009.
[http://dx.doi.org/10.1007/978-3-642-04944-6_14]
[16]
Mirjalili S, Mirjalili SM, Lewis A. Grey Wolf optimizer. Adv Eng Softw 2014; 69: 46-61.
[http://dx.doi.org/10.1016/j.advengsoft.2013.12.007]
[17]
Mirjalili S. Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm. Knowledge-Based Syst 2015; 89: 228-49.
[http://dx.doi.org/10.1016/j.knosys.2015.07.006]
[18]
Mirjalili S, Lewis A. The whale optimization algorithm. Adv Eng Softw 2016; 95: 51-67.
[http://dx.doi.org/10.1016/j.advengsoft.2016.01.008]
[19]
Saremi S, Mirjalili S, Lewis A. Grasshopper optimization algorithm: Theory and application. Adv Eng Softw 2017; 105: 30-47.
[http://dx.doi.org/10.1016/j.advengsoft.2017.01.004]
[20]
Mirjalili S, Gandomi AH, Mirjalili SZ, Saremi S, Faris H, Mirjalili SM. Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems. Adv Eng Softw 2017; 114: 163-91.
[http://dx.doi.org/10.1016/j.advengsoft.2017.07.002]
[21]
Li S, Chen H, Wang M, Heidari AA, Mirjalili S. Slime mould algorithm: A new method for stochastic optimization. Future Gener Comput Syst 2020; 111: 300-23.
[http://dx.doi.org/10.1016/j.future.2020.03.055]
[22]
Sarkar S. Hong-Hsu Yen, Dixit S, Mukherjee B. Hybrid wireless-optical broadband access network (WOBAN): Network planning and setup. IEEE J Sel Areas Comm 2008; 26(6): 12-21.
[http://dx.doi.org/10.1109/JSACOCN.2008.032207]
[23]
Zheng Z, Wang J, Wang X. ONU placement in fiber-wireless (FiWi) networks considering peer-to-peer communications. Proceeding of Global Telecommunications Conference (GLOBECOM). 2009 30 Nov- 04 Dec; Honolulu, HI, USA: IEEE. 2009.
[24]
Bhatt UR, Chouhan N, Upadhyay R. Hybrid algorithm: A cost efficient solution for ONU placement in Fiber-Wireless (FiWi) network. Opt Fiber Technol 2015; 22: 76-83.
[http://dx.doi.org/10.1016/j.yofte.2015.01.010]
[25]
Bhatt UR, Upadhyay R, Kothari D, et al. Cost Efficient low convergence ONU placement algorithm for deployment of FiWi network. TOEOC 2016; 6: 1-17.
[26]
Bhatt UR, Chouhan N, Upadhyay R, Agrawal C. ONU Placement in FiWi access network using teacher phase of TLBO algorithm. Proceeding of 3rd International Conference on Computational Intelligence & Communication Technology (CICT). 2017 Feb 9-10; Ghaziabad, India: IEEE. 2017.
[27]
Bhatt UR, Upadhyay R, Chhabra A, Chouhan N. Efficient Placement of ONUs via Ant colony optimization algorithm in FiWi access networks. Advances in Intelligent Systems and Computing AISC Series of Springer 2016; 563: 521-8.
[28]
Chouhan N, Bhatt UR, Upadhyay R. Reduction in Average Distance Cost by Optimizing Position of ONUs in FiWi Access Network using Grey Wolf Optimization Algorithm. Lecture Notes Electr Eng 2021; 735: 91-104.
[http://dx.doi.org/10.1007/978-981-33-6977-1_8]
[29]
Bhatt UR, Dhakad A, Chouhan N, Upadhyay R. Fiber wireless (FiWi) access network: ONU placement and reduction in average communication distance using whale optimization algorithm. Heliyon 2019; 5(3): e01311.
[http://dx.doi.org/10.1016/j.heliyon.2019.e01311] [PMID: 30976667]
[30]
Chouhan N, Bhatt UR, Upadhyay R. Potential Sites searching for ONUs in FiWi network. Proceedings of Recent Advances in Interdisciplinary Trends in Engineering & Applications (RAITEA); 2019 Feb 14; Indore, India: SSRN 2019.
[http://dx.doi.org/10.2139/ssrn.3364212]
[31]
Chouhan N, Bhatt UR, Upadhyay R. Performance Evaluation of Fiber Wireless (FiWi) Access Network using Position Optimization of ONUs. Int J Sens Wirel Commun Control 2020; 11(3): 2020.
[32]
Chouhan N, Bhatt UR, Upadhyay R. An optimization framework for FiWi access network: Comprehensive solution for green and survivable deployment. Opt Fiber Technol 2019; 53: 102002.
[http://dx.doi.org/10.1016/j.yofte.2019.102002]
[33]
Chouhan N, Bhatt UR, Upadhyay R. Weighted Salp Swarm and Salp Swarm Algorithms in FiWi access network: A new paradigm for ONU placement. Opt Fiber Technol 2021; 63: 102505.
[http://dx.doi.org/10.1016/j.yofte.2021.102505]
[34]
Wolpert DH, Macready WG. No free lunch theorems for optimization. IEEE Trans Evol Comput 1997; 1(1): 67-82.
[http://dx.doi.org/10.1109/4235.585893]
[35]
Abualigah L, Geem ZW. Reptile Search Algorithm (RSA): A nature inspired meta-heuristic optimizer. Expert Syst Appl 2021; 191: 116158.

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy