Enhancement of Quality of Service (QoS) in Internet of Things based on big data environment using the Harris Hawks algorithm - Sefati, Seyed Salar; Halunga, Simona (SPIE, 2023)
The Internet of Things (IoT) is a new technology that employs a variety of sensors and wireless communication protocols. People are leveraging IoT to make their lives easier by using innovative and intelligent equipment. This paper presents a new approach, developed in order to increase the reliability in the IoT using the Harris Hawks Optimization (HHO) algorithm in a big data environment. Reliability and availability in big data represents critical criteria for selecting the most suitable protocol. Also, in most scenarios, the sensors' battery cannot be replaced, so energy consumption is another important issue in such IoT system. This research provides an enhanced artificial intelligence approach, based on the HHO technique, to handle load balancing between the Cluster Heads (CH) in a big data environment. A proper load balancing between CHs is vital in sensor network communication since it reduces the energy consumption of the devices. The HHO algorithm selects the appropriate CH by using a hunting technique, that is divided into 2 categorizes, soft besiege and hard besiege. The hunting depends on the remaining energy of the rabbit; at first, rabbit energy is high, but, after a while, the energy of rabbit decreases, so the Harris Hawks attack to this animal in soft besiege. Using this technique, we have tried to balance the energy and reliability of the Internet of Things between CHs. This proposed method was simulated on Network Simulator 3 (NS3).