An Energy Efficient Path Selection Using Swarm Intelligence in IoT SN

Abstract

IoT is regarded as one of future technology’s most important fields and is receiving significant interest from a wide variety of applications. Nowadays, with the emergence of smart objects, the quantity of things that are associated with the web is expanding dramatically. In IoT, there are many critical problems such as scalability, load balancing, tolerance for faults, energy utilization, etc. A few steering conventions have been created to meet the Internet of Things details for various models, for example, energy utilization, load adjusting, multicasting, network life expectancy, unwavering quality, and versatility. Another directing calculation dependent on the insect settlement calculation is proposed to locate the ideal course of information transmission in the IOT. In Swarm Intelligence, Ant-Colony Optimization algorithm is a procedure used to address computational issues that can be utilized to locate an ideal way and subsequently devour less energy. Results of simulation show that the new ant-colony algorithm can successfully saves node energy and broaden the life of the system.