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International Journal of Sensors, Wireless Communications and Control

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

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Research Article

Imposing Packet Relaying for Mobile Adhoc Networks Using Genetic Algorithm

Author(s): Prasanna Venkatesan Theerthagiri*

Volume 10, Issue 4, 2020

Page: [617 - 624] Pages: 8

DOI: 10.2174/2210327910666200320090234

Price: $65

Abstract

Background: Packet forwarding is an essential network operation in wireless networks to establish communication among wireless devices. In mobile wireless networks, data transmission occurs in the form of packet relaying. In dynamic environmental networks, relaying of the packet is a more complex process and much essential activity.

Objective: It requires the co-operation of intermediate nodes in the network. Specifically, in Mobile Adhoc Networks (MANET) it is the most tedious job because of its dynamic topology, limited energy, and other resource constraints. In this paper, a genetic algorithm is adopted for stimulating the packet relaying, such that to assist the co-operation between various nodes in the network.

Methods: The genetic algorithm is a metaheuristic process-based evolutionary algorithms. It intends to produce high-quality optimized solutions to any given complex problems. The current research work had carried out an extensive investigation and comparison of existing relevant genetic algorithm based algorithms.

Results: The experimental results are evaluated based on the methodology of the genetic algorithm, the number of nodes, robustness, scalability, packet delivery ratio, average energy consumption, and other parameters.

Keywords: Co-operative communication, genetic algorithm, MANETs, routing, optimization, heuristic algorithm.

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[1]
Seredynski M, Bouvry P. Analysing the development of cooperation in MANETs using evolutionary game theory. J Supercomput 2013; 63: 854-70.
[2]
Rania S, Malhotrab J, Talwarca R. Energy-efficient chain based cooperative routing protocol for WSN. Appl Soft Comput 2015; 35: 1-12.
[http://dx.doi.org/10.1016/j.asoc.2015.06.034]
[3]
Prasannavenkatesan T, Raja R, Ganeshkumar P. PDA-misbehaving node detection & prevention for MANETs. 2014 International Conference on Communication and Signal Processing. Melmaruvathur, India. 2014.
[4]
Vamsi PR, Kant K. Trust and location-aware routing protocol for wireless sensor networks. J Inst Electron Telecommun Eng 2016; 62(5): 634-44.
[http://dx.doi.org/10.1080/03772063.2016.1147389]
[5]
Kusyk J, Sahin CS, Uyar MU, Urrea E, Gundry S. Self-organization of nodes in mobile ad hoc networks using evolutionary games and genetic algorithms. J Adv Res 2011; 2(3): 253-64.
[http://dx.doi.org/10.1016/j.jare.2011.04.006]
[6]
Sukumaran S, Venkatesh J, Korath A. Stimulating Cooperation in Mobile Ad hoc Networks using Cut Diamond with Diamond method. Int J Comput Sci Issues 2012; 9(2): 3.
[7]
Jain S, Sahu S. The application of genetic algorithm in the design of routing protocols in MANETs: A survey. Int J Comput Sci IT 2012; 3(3): 4318-21.
[8]
Omrani A, Fallah MS. Stimulating cooperation in MANETs using game theory. Proceedings of the World Congress on Engineering 2007.
[9]
Yen YS, Chao HC, Chang RS, Vasilakos A. Flooding-limited and multi-constrained QoS multicast routing based on the genetic algorithm for MANETs. Math Comput Model 2011; 53: 2238-50.
[http://dx.doi.org/10.1016/j.mcm.2010.10.008]
[10]
Potukuchi R, Kant K. Detecting location-based attacks in WSN using sequential analysis. J Inst Electron Telecommun Eng 2015; 61(5): 541-51.
[http://dx.doi.org/10.1080/03772063.2015.1025111]
[11]
Ting CK. On the mean convergence time of multi-parent genetic algorithms without selection. Adv Artific Life 2005; 3630: 403-12.
[12]
Rahnamay-Naeini M, Sabaei M. A combinational perspective in stimulating cooperation in mobile ad hoc networks. J Comput Sci Technol 2011; 26(2): 256-68.
[http://dx.doi.org/10.1007/s11390-011-9432-7]
[13]
Komali RS, MacKenzie AB. Impact of selfish packet forwarding on energy-efficient topology control 2008. 6th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks and Workshops. Berlin, Germany, 2008.
[14]
Lu T, Zhu J. Genetic algorithm for energy-efficient QoS multicast routing. IEEE Commun Lett 2013; 17(1): 31-4.
[http://dx.doi.org/10.1109/LCOMM.2012.112012.121467]
[15]
Tang C, Li A, Li X. When reputation enforces evolutionary cooperation in unreliable MANETs. IEEE Trans Cybern 2015; 45(10): 2190-201.
[16]
Yang S, Cheng H, Wang F. Genetic algorithms with immigrants and memory schemes for dynamic shortest path routing problems in Mobile Ad Hoc networks. IEEE T SYST MAN CY C 2010; 40(1): 52-63.
[17]
Arghavani A, Arghavani M, Sargazi A, Ahmadi M. Modeling & stimulating node cooperation in Wireless AdHoc Networks. ETRI J 2015; 37(1): 1-13.
[http://dx.doi.org/10.4218/etrij.15.0113.1371]
[18]
Prasanna VT, Rajakumar P, Pitchaikkannu A. Overview of proactive routing protocols in MANET. 2014 Fourth International Conference on Communication Systems and Network Technologies. Bhopal, India. 2014.
[19]
Mohammad T, Mahsa P, Mehran Y, Hadi BM. An efficient algorithm for function optimization: Modified stem cells algorithm. Cent Eur J Eng 2012; 3(1): 36-50.
[20]
Patrascu M, Stancu AF, Pop F. HELGA: A heterogeneous encoding lifelike genetic algorithm for population evolution modeling and simulation. Soft Comput 2014; 18: 2565-76.
[http://dx.doi.org/10.1007/s00500-014-1401-y]
[21]
Zhang G, Wu M, Duan W, Huang X. Genetic algorithm based QoS perception routing protocol for VANETs. Wirel Commun Mob Comput 2018.
[http://dx.doi.org/10.1155/2018/3897857]
[22]
Biradar A, Thool RC. Reliable genetic algorithm based intelligent routing for MANET. 2014 World Congress on Computer Applications and Information Systems (WCCAIS) Hammamet, Tunisia 2014.
[http://dx.doi.org/10.1109/WCCAIS.2014.6916649]
[23]
Zhang DG, Liu S, Liu XH, Zhang T, Cui YY. Novel Dynamic Source Routing protocol (DSR) based on Genetic Algorithm‐Bacterial Foraging Optimization (GA‐BFO). Int J Commun Syst 2018; 31(18)e3824
[http://dx.doi.org/10.1002/dac.3824]
[24]
Theerthagiri P. CoFEE: Context‐aware futuristic energy estimation model for sensor nodes using Markov model and autoregression. Int J Commun Syst 2019; 2019e4248
[http://dx.doi.org/10.1002/dac.4248]
[25]
Suraj R, Tapaswi S, Yousef S, Pattanaik KK, Cole M. Mobility prediction in mobile ad hoc networks using a lightweight genetic algorithm. Wirel Netw 2016; 22(6): 1797-806.
[http://dx.doi.org/10.1007/s11276-015-1059-0]
[26]
Dhurandher SK, Sharma DK, Woungang I, Gupta R, Garg S. GAER: Genetic algorithm-based energy-efficient routing protocol for infrastructure-less opportunistic networks. J Supercomput 2014; 69(3): 1183-214.
[http://dx.doi.org/10.1007/s11227-014-1195-9]
[27]
Preetha V, Chitra K. ZBMRP: Zone based MANET routing protocol with genetic algorithm and security enhancement using neural network learning. Int J Netw Secur 2018; 20(6): 1115-24.
[28]
Singh S, Koslia M, Poonia RCAGA-QMR. Genetic algorithm oriented MANET QoS multicast routing. Recent Pat Comput Sci 2018; 11(4): 268-75.
[http://dx.doi.org/10.2174/2213275911666181008150256]
[29]
Rajan C, Shanthi N. Genetic based optimization for multicast routing algorithm for MANET. Sadhana 2015; 40(8): 2341-52.
[http://dx.doi.org/10.1007/s12046-015-0437-8]
[30]
Theerthagiri P, Thangavelu M. Futuristic speed prediction using auto‐regression and neural networks for mobile ad hoc networks. Int J Commun Syst 2019; 32(9)e3951
[http://dx.doi.org/10.1002/dac.3951]
[31]
Prabha R, Ramaraj N. An improved multipath MANET routing using link estimation and swarm intelligence. EURASIP J Wirel Commun Netw 2015; 2015(1): 173.
[http://dx.doi.org/10.1186/s13638-015-0385-3]
[32]
Theerthagiri P. FUCEM: Futuristic cooperation evaluation model using Markov process for evaluating node reliability and link stability in mobile ad hoc network. Wirel Netw 2020; 26: 4173-88.
[http://dx.doi.org/10.1007/s11276-020-02326-y]

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