A Cognitive Based Channel Assortment Using Ant-Colony Optimized Stable Path Selection in an IoTN

Abstract

Routing protocols have ability to discover and maintain routes in the network. However, the efficiency of designed routing protocol depends on the node capability and application requirement. IoTN (Internet of Things Network) is being adopted into real time applications such as finding shortest path to reach destination, traffic management, rerouting path based on weather conditions, happy home architectures, weather systems and so on. Despite enormous applications of IoTN, the battery life and energy efficiency are limited to fulfil applications in IoTN. Hence the selected features for the proposed algorithm contribute towards optimizing the path to select best and least distance path to destination using ant-based system. Proposed Ant-colony optimized stable path (AOSP) selection algorithm focus on network selection stages like Selection of acquaintances, channel decisions and Energy management. Sensors can communicate with target BS (Base station) to forward or relay the data efficiently to reach server. The optimal intermediate sensors can act as cluster head and collect information from group of sensors with minimal energy spent which increase the throughput and decrease the packet dropping ratio.