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http://dx.doi.org/10.3837/tiis.2015.09.012

Recurrent Ant Colony Optimization for Optimal Path Convergence in Mobile Ad Hoc Networks  

Karmel, A (Anna University of Technology)
Jayakumar, C (Department of Computer Science & Engineering RMK Engineering College)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.9, no.9, 2015 , pp. 3496-3514 More about this Journal
Abstract
One of the challenging tasks in Mobile Ad hoc Network is to discover precise optimal routing solution due to the infrastructure-less dynamic behavior of wireless mobile nodes. Ant Colony Optimization, a swarm Intelligence technique, inspired by the foraging behaviour of ants in colonies was used in the past research works to compute the optimal path. In this paper, we propose a Recurrent Ant Colony Optimization (RECACO) that executes the actual Ant Colony Optimization iteratively based on recurrent value in order to obtain an optimal path convergence. Each iteration involves three steps: Pheromone tracking, Pheromone renewal and Node selection based on the residual energy in the mobile nodes. The novelty of our approach is the inclusion of new pheromone updating strategy in both online step-by-step pheromone renewal mode and online delayed pheromone renewal mode with the use of newly proposed metric named ELD (Energy Load Delay) based on energy, Load balancing and end-to-end delay metrics to measure the performance. RECACO is implemented using network simulator NS2.34. The implementation results show that the proposed algorithm outperforms the existing algorithms like AODV, ACO, LBE-ARAMA in terms of Energy, Delay, Packet Delivery Ratio and Network life time.
Keywords
Ant Colony Optimization (ACO); MANET; End-to-End Delay; Energy; Load Balancing;
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