The proliferations of IoT technologies and
applications have led to an increased interest in Wireless Sensor
Networks (and in particular, multi-hop networks). Wireless sensor
networks are composed of small mobile terminals which have
limited system resources. Due to this, these networks are
vulnerable to changes in network status arising from changes in
the network parameters such as, position / layout of sensors,
signal strength, environmental conditions, etc. In addition, the
network nodes are also constrained in terms of energy provided by
the battery. It is an significant consideration to be accounted so as
to prolong their operational time, since this adds to the network
lifetime. Lot of research has gone into routing and transmission
technologies for wireless sensor networks. Conventional routing
mechanisms for WSNs still suffer from energy-hole problem
caused by difficulties in adaptive route management. Thus, it is
imperative that efficient routing mechanisms be developed in
order to conserve energy and improve network lifetime. One
popular approach is to use meta-heuristic algorithms for optimal
path selection in a WSN route management system. A very
popular meta-heuristic algorithm used for this objective is the Ant
Colony Optimization (ACO) algorithms. ACO has been used as a
base for many routing management systems. In this paper an
extensive analysis of the performance of ACO based route
selection mechanism is reported and also reporting a comparative
analysis of efficacy of the ACO routing algorithm over the
standard Greedy algorithm in finding routes with different count
of sensor nodes and different count of ants. Then find that the
ACO routing algorithm outdoes the Greedy algorithm with respect
to the number of routes identified.