A Mobile Adhoc network is a collection of nodes that are dynamically and arbitrarily located in such a manner that the inter connections between nodes are capable of changing on a continual basis. Ad hoc wireless networks are increasing in popularity, because of the spread of laptops, sensor devices, personal digital assistants, and other mobile electronic devices, these devices will eventually need to communicate with each other. For the implementation of MANET, the important factor which is concern is the routing of data from source to destination via various nodes as a mediator due to mobility of mobile nodes. Since the nodes are mobile, the network topology may change rapidly and unpredictably over time. The network topology is u structured and nodes may enter or leave at their will. For mobile ad hoc networks, the complexity of routing increases because of its characteristics such as dynamic topology, absence of centralized authority, time varying quality of service (QoS) requirements, etc. Ant Colony Optimization (ACO) algorithm uses mobile agents as ants to discover feasible and best path in a network. ACO helps in finding the paths between two nodes in a network and selection of path can be changed dynamically according to co dition of the wireless network in case of network congestion.
Published in |
American Journal of Networks and Communications (Volume 4, Issue 3-1)
This article belongs to the Special Issue Ad Hoc Networks |
DOI | 10.11648/j.ajnc.s.2015040301.19 |
Page(s) | 54-56 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
pheromones, trail, bandwidth, routing and load distribution, MANET, Ant Colony Optimization
[1] | “Ant Colony based Routing for Mobile Ad-Hoc Networks towards Improved Quality of Services.” Bibhash Roy, Suman Banik, Parthi Dey and Sugata Sanyal |
[2] | “An ant colony-based multi objective quality of service routing for mobile ad hoc networks.” Perumalsamy Deepalakshmi and Shanmugasundaram Radhakrishnan |
[3] | “Review of AODV protocol for QoS Routing in MANET’s” Sukhveer Kaur, Mr. Vinay Bhardwaj |
[4] | “MALBACO - A New Multi-Agent Load Balanced Ant Colony Optimization Algorithm for MANETs” Ditipriya Sinha and Rituparna Chaki |
[5] | “MANET link Performance using Ant Colony Optimization and Particle Swarm Optimization Algorithms” B.Nancharaiah B.Chandra Mohan |
[6] | “Application Research Based Ant Colony Optimization for MANET” Xiang Yang, Li Layuan, Cheng Chuanhui |
[7] | “New approach for routing in mobile ad-hoc networks based on ant colony optimization with global positioning system”. Deepak C. Karia, Vaibhav V. Godbole |
APA Style
Somesh Maheshwari, Manish Bhardwaj. (2015). Secure Route Selection in Manet Using Ant Colony Optimization. American Journal of Networks and Communications, 4(3-1), 54-56. https://doi.org/10.11648/j.ajnc.s.2015040301.19
ACS Style
Somesh Maheshwari; Manish Bhardwaj. Secure Route Selection in Manet Using Ant Colony Optimization. Am. J. Netw. Commun. 2015, 4(3-1), 54-56. doi: 10.11648/j.ajnc.s.2015040301.19
AMA Style
Somesh Maheshwari, Manish Bhardwaj. Secure Route Selection in Manet Using Ant Colony Optimization. Am J Netw Commun. 2015;4(3-1):54-56. doi: 10.11648/j.ajnc.s.2015040301.19
@article{10.11648/j.ajnc.s.2015040301.19, author = {Somesh Maheshwari and Manish Bhardwaj}, title = {Secure Route Selection in Manet Using Ant Colony Optimization}, journal = {American Journal of Networks and Communications}, volume = {4}, number = {3-1}, pages = {54-56}, doi = {10.11648/j.ajnc.s.2015040301.19}, url = {https://doi.org/10.11648/j.ajnc.s.2015040301.19}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnc.s.2015040301.19}, abstract = {A Mobile Adhoc network is a collection of nodes that are dynamically and arbitrarily located in such a manner that the inter connections between nodes are capable of changing on a continual basis. Ad hoc wireless networks are increasing in popularity, because of the spread of laptops, sensor devices, personal digital assistants, and other mobile electronic devices, these devices will eventually need to communicate with each other. For the implementation of MANET, the important factor which is concern is the routing of data from source to destination via various nodes as a mediator due to mobility of mobile nodes. Since the nodes are mobile, the network topology may change rapidly and unpredictably over time. The network topology is u structured and nodes may enter or leave at their will. For mobile ad hoc networks, the complexity of routing increases because of its characteristics such as dynamic topology, absence of centralized authority, time varying quality of service (QoS) requirements, etc. Ant Colony Optimization (ACO) algorithm uses mobile agents as ants to discover feasible and best path in a network. ACO helps in finding the paths between two nodes in a network and selection of path can be changed dynamically according to co dition of the wireless network in case of network congestion.}, year = {2015} }
TY - JOUR T1 - Secure Route Selection in Manet Using Ant Colony Optimization AU - Somesh Maheshwari AU - Manish Bhardwaj Y1 - 2015/02/12 PY - 2015 N1 - https://doi.org/10.11648/j.ajnc.s.2015040301.19 DO - 10.11648/j.ajnc.s.2015040301.19 T2 - American Journal of Networks and Communications JF - American Journal of Networks and Communications JO - American Journal of Networks and Communications SP - 54 EP - 56 PB - Science Publishing Group SN - 2326-8964 UR - https://doi.org/10.11648/j.ajnc.s.2015040301.19 AB - A Mobile Adhoc network is a collection of nodes that are dynamically and arbitrarily located in such a manner that the inter connections between nodes are capable of changing on a continual basis. Ad hoc wireless networks are increasing in popularity, because of the spread of laptops, sensor devices, personal digital assistants, and other mobile electronic devices, these devices will eventually need to communicate with each other. For the implementation of MANET, the important factor which is concern is the routing of data from source to destination via various nodes as a mediator due to mobility of mobile nodes. Since the nodes are mobile, the network topology may change rapidly and unpredictably over time. The network topology is u structured and nodes may enter or leave at their will. For mobile ad hoc networks, the complexity of routing increases because of its characteristics such as dynamic topology, absence of centralized authority, time varying quality of service (QoS) requirements, etc. Ant Colony Optimization (ACO) algorithm uses mobile agents as ants to discover feasible and best path in a network. ACO helps in finding the paths between two nodes in a network and selection of path can be changed dynamically according to co dition of the wireless network in case of network congestion. VL - 4 IS - 3-1 ER -