Abstract

Ant Colony Optimization (ACO) (Deepalakshmi & Radhakrishnan, 2009; Sharma & Kotecha, 2011; Sharma, Karkhanawala, & Kotecha, 2011) is a meta-heuristic, suitable for optimized solutions to routing problem in Mobile Adhoc Networks (MANETs). ACO based algorithms are fully distributed, self-organizing, fault tolerant, and intrinsically adapts to changing traffic patterns. However, if the best path is preferred for routing over longer period of time, the exploratory behaviour of the ants may be affected, thus leading to stagnation of the best paths. The authors have reviewed various techniques used for stagnation control and avoidance (Li, Ma, & Cao, 2005). These include, Pheromone control (Schoonderwoerd, Holland, Bruten, & Rothkrantz, 1996; Wedde & Farooq, 2006; De Rango & Socievole, 2011), Pheromone heuristics control (Sim & Sun, 2003), Privileged pheromone laying (Wedde & Farooq, 2006; Stuzle & Hoos, 2000), Multiple ant colony optimization (De Rango & Socievole, 2011; Sim & Sun, 2003), and Multiple path routing (Upadhyaya & Setiya, 2009b) techniques. They also present a comparative analysis of these schemes with respect to the parameter on which they depend for stagnation avoidance. The paper also focuses on stagnation leading to losses of data, which can lay a drastic effect on the quality of multimedia transmission. The authors propose a scheme to improve the exploratory behaviour of ants, by paralleled release of two streams of forward ants in each iteration, along the path from source to destination. It is mentioned that the technique will improve the quality of multimedia routed through MANETs, due to the multipath based enhancements.

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