Hybrid Ant Colony and Cuckoo Seach Optimization Protocol for Wsn Assisted Iot Based Agricultural Application

Abstract

Abstract Internet of Things (IoT) has been observed these days in variety of applications where the devices interconnect with each other using Internet and provide much useful information for various purposes. These network are often backed by WSNs where sensors play a significant part in gathering environmental data; this data is processed and used by IoT devices for numerous applications. This paper proposes agricultural application of IoT where the soil moisture content is continuously monitored such that excess watering can be avoided; this leads to water conservation in addition to preventing the crop damage. Furthermore, sensors also monitor the environmental parameters which are responsible for causing fire in the fields. This information is sent to the server where it can be processed and damage to crops can be avoided. The clustering approach has been suggested for underlying sensor system where the main objective function of augmenting the network lifetime and reducing the data delivery delay has been laid out. The cuckoo search optimization (CS) has been used in unison with ant colony algorithm (ACO) to select the optimal cluster heads. The traffic heterogeneity scenario has been considered in the network where the fire sensors has more data to forward to base station as compared to moisture sensors; this traffic heterogeneity has been primarily considered which choosing the optimal CH. Furthermore, the information transmission process from CH to BS is also optimized by forming the paths using ACO and selecting one best out of them for data forwarding. The suggested approach was experiment in MATLAB & contrasted compared with other protocols namely GWO, ESO, GECR and LEACH based on average residual energy of the system, network stability, network lifetime and delivery delay. The suggested approach has managed to achieve good system lifespan & less delivery delays.