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IAR: Bio Inspired Intelligent Ant Routing Algorithm for Mobile Ad-Hoc Networks


Affiliations
1 Sona College of Technology, Salem, India
     

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The paper presents a novel proactive algorithm for routing called Intelligent Ant Routing (IAR), in mobile ad hoc networks, which is inspired by Ant Colony Optimization (ACO) framework and uses "ants" for route discovery, maintenance and improvement. The design for the protocol lies in a heuristic, based on bio inspired routing, which takes into account the limited resources in highly dynamic environment. The algorithm is based on a modification of the state transition rule of ACO routing algorithm which results in maintaining higher degree of investigation leads to reduced end-to-end delay and also lowers the overhead at high node density. The comparative result of proposed algorithm IAR with AODV reactive routing algorithm exhibits superior performance with respect to reactive AODV routing algorithm in terms of end-to end delay. It is also tested for different network sizes and node mobility.

Keywords

Intelligent Ant Routing, Mobile Ad Hoc Networks, Ant Colony Optimization (ACO), Ad Hoc on Demand Distance Vector Routing (AODV).
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  • IAR: Bio Inspired Intelligent Ant Routing Algorithm for Mobile Ad-Hoc Networks

Abstract Views: 141  |  PDF Views: 3

Authors

J. SujiPriya
Sona College of Technology, Salem, India
R. Shanthy
Sona College of Technology, Salem, India
T. Padma
Sona College of Technology, Salem, India

Abstract


The paper presents a novel proactive algorithm for routing called Intelligent Ant Routing (IAR), in mobile ad hoc networks, which is inspired by Ant Colony Optimization (ACO) framework and uses "ants" for route discovery, maintenance and improvement. The design for the protocol lies in a heuristic, based on bio inspired routing, which takes into account the limited resources in highly dynamic environment. The algorithm is based on a modification of the state transition rule of ACO routing algorithm which results in maintaining higher degree of investigation leads to reduced end-to-end delay and also lowers the overhead at high node density. The comparative result of proposed algorithm IAR with AODV reactive routing algorithm exhibits superior performance with respect to reactive AODV routing algorithm in terms of end-to end delay. It is also tested for different network sizes and node mobility.

Keywords


Intelligent Ant Routing, Mobile Ad Hoc Networks, Ant Colony Optimization (ACO), Ad Hoc on Demand Distance Vector Routing (AODV).