Efficient routing protocol in IoT using modified Genetic algorithm and its comparison with existing protocols

With the advancements in the field of Internet of things (IoT), the scope for research and development of wireless mesh network (WMN) and wireless sensor networks (WSN) has grown drastically. Routing of data in a network is a crucial task, and a significant amount of energy can be saved if the routing is done effectively in a network which is an optimization problem with many constraints like path, energy in a node, link quality, traffic, etc. In order to solve such problems, Genetic Algorithms (GA) that includes heuristic techniques over the given network population would provide a convincing optimized solution. However, the performance of such algorithm is hindered due to premature convergence, hence are incapable of traversing the search space to have numerous solutions for better energy saving. In order to tackle such drawbacks, an enhanced Genetic Algorithm using Local Search technique can be adapted. In this paper, we propose a modified GA called as MEGA (Maximum Enhanced Genetic Algorithm) using Local Search mechanism along with Sleep-Wake up mechanism. It optimizes the Wireless Sensor Network such that the energy conservation and extension of network lifetime takes place dynamically, by considering the communication constraints and energy consumption of sensors during their operation and communication. We compare our proposed MEGA protocol with a few existing routing protocols to check its efficiency in terms of routing performance and energy consumption. Development and performance analysis of ad-hoc networking protocols is realized using software-based simulation tools and performance of the system is evaluated for different networking scenario and conditions of WSN with improved energy saving and routing efficiency.