Internet of things: Route search optimization applying ant colony algorithm and theory of computation

Abstract

Internet of Things (IoT) possesses a dynamic network where the network nodes (mobile devices) are added and removed constantly and randomly; hence, the traffic distribution in the network is quite variable and irregular. The basic but very important part in any network is route searching. We have many conventional route searching algorithms such as link-state and distance vector algorithms, but they are restricted to the static point-to-point network topology. In this paper, we proposed a hypothetical but feasible model that uses the ant colony optimization (ACO) algorithm for route searching. ACO is dynamic in nature and has a positive feedback mechanism that conforms to the route searching. In addition, we have embedded the concept of deterministic finite automata (DFA) minimization to minimize the number of iterations done by ACO in finding the optimal path from source to sink. Analysis and proof show that ACO gives the shortest optimal path from the source to the destination node, and DFA minimization reduces the broadcasting storm effectively. © Springer India 2015.