Analysis of Routing Algorithms based on the Natural Inspiration

Analysis of Routing Algorithms based on the Natural Inspiration

H.Fathima Assistant professor

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H. Fathima

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Periyar University

Analysis of Routing Algorithms based on the Natural Inspiration

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Abstract

Nature is a great and immense source of inspiration for solving hard and complex problems in computer science since it exhibits extremely diverse, dynamic, robust, complex and fascinating phenomenon. Nature inspired algorithms are metaheuristics that mimics the nature for solving optimisation problems opening a new era in computation. A new agent-based routing algorithm using optimisation techniques is implemented in this paper. The different optimisation techniques are warty frog fish, artificial ant, ant, ant lion, grey wolf, genetic algorithm (GA) are the combinations used in the packet delivery between the networks. The routing is a process of carrying the data from source to destination in the network. The output of these algorithms is determined by the simulation time. The experiments are implemented with the NS2 software platform, which is based on the basics of C, C++ and TCL scripting language. The results of the algorithm showed that the grey wolf optimiser (GWO) is much better than the other algorithms in the packet delivery between the networks.

References

29 Cites in Article

Reference Format

Seyedali Mirjalili,Seyed Mirjalili,Andrew Lewis (2014). Grey Wolf Optimizer.
C Muro,R Escobedo,L Spector,R Coppinger (2011). Wolfpack (Canis lupus) hunting strategies emerge from simple rules in computational simulations.
Seyedali Mirjalili (2015). How effective is the Grey Wolf optimizer in training multi-layer perceptrons.
Nipotepat Muangkote,Khamron Sunat,Sirapat Chiewchanwattana (2014). An improved grey wolf optimizer for training q-Gaussian Radial Basis Functional-link nets.
Lo Wong,Ing (2014). Grey Wolf Optimizer for solving economic dispatch problems.
Hong Song,Mohd Mee,Mohd Herwan Sulaiman,Mohamed Rusllim (2014). An Application of Grey Wolf Optimizer for Solving Combined Economic Emission Dispatch Problems.
E Emary (2015). Feature Subset Selection Approach by Gray-Wolf Optimization.
El-Gaafary,A Ahmed (2015). Grey Wolf Optimization for Multi Input Multi Output System.
Shahrzad Saremi,Seyedeh Mirjalili,Seyed Mirjalili (2014). Evolutionary population dynamics and grey wolf optimizer.
Sarah Carrow (2007). Microhabitat Selection and Pit Effectiveness of Myrmeleon Immaculatus Degeer Antlion Larvae in Western Kansas.
Sarah Carrow (2007). Microhabitat Selection and Pit Effectiveness of Myrmeleon Immaculatus Degeer Antlion Larvae in Western Kansas.
Mark Swanson (2007). Antlion" in the World's Languages.
Robert Miller,Lionel Stange (2015). Glenurus gratus (Say) (Insecta: Neuroptera: Myrmeleontidae).
Jean-Henri Fabre (2013). Fabre, Jean-Henri Casimir.
Donya Camp (2005). Beneficials in the garden: Antlion.
Marc Staniszewski (1998). Madagascan Burrowing Frogs: Genus: Scaphiophryne(Boulenger, 1882).
M; Venesci,C Raxworthy,R Nussbaum,F Glaw (2003). A revision of theScaphiophryne marmorata complex of marbled toads from Madagascar, including the description of a new species" (PDF).
W Federle,W Barnes,W Baumgartner,P Drechsler,J Smith (2006). Wet but not slippery: boundary friction in tree frog adhesive toe pads.
Doris Cochran,Mabel (1961). Living Amphibians of the World.
Phyllomedusa ayeaye.
Sharon Emerson,M Koehl (1990). The Interaction of Behavioral and Morphological Change in the Evolution of a Novel Locomotor Type: "Flying" Frogs.
F Ravary,E Lecoutey,G Kaminski,N Châline,P Jaisson (2007). Individual experience alone can generate lasting division of labor in ants.
Nigel Franks,James Hooper,Catherine Webb,Anna Dornhaus (2005). Tomb evaders: house-hunting hygiene in ants.
Bert Hölldobler,Edward Wilson (1990). The Army Ants.
Simon Robson,Rudolf Kohout (2005). Evolution of nest‐weaving behaviour in arboreal nesting ants of the genus <i>Polyrhachis</i> Fr. Smith (Hymenoptera: Formicidae).
M Dorigo,M Birattari,T Stützle (2006). Ant Colony Optimization: Artificial Ants as a Computational Intelligence Technique.
Mohd Murtadha,Mohamad (2008). Articulated Robots Motion Planning Using Foraging Ant Strategy.
(2010). Artificial Ants.
A Kazharov,V Kureichik (2010). Ant colony optimization algorithms for solving transportation problems.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

H.Fathima. 2016. \u201cAnalysis of Routing Algorithms based on the Natural Inspiration\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 16 (GJCST Volume 16 Issue E2): .

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GJCST Volume 16 Issue E2
Pg. 25- 32

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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Classification

GJCST-E Classification: C.2.2 C.2.1

Submission ReceivedDecember 9, 2015
Peer Review Double Blind
Handling Editor
Accepted December 31, 2015
Published January 15, 2016

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v1.2

Issue date

April 18, 2016

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Article Matrices

Total Score: 101

Country: Unknown

Subject: Global Journal of Computer Science and Technology - E: Network, Web & Security

Authors: H. Fathima (PhD/Dr. count: 0)

View Count (all-time): 259

Total Views (Real + Logic): 7561

Total Downloads (simulated): 2015

Publish Date: 2016 04, Mon

Monthly Totals (Real + Logic):

Month 1: 43 views
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Total Views: 7561

Total Downloads: 2015

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