Optimization Method based Efficient Techniques for Enhancing the Qos Parameters in WSN-Iot

Abstract

Wireless networks are made up of many low-cost nodes, most of which can only sense, calculate, and talk to a few other nodes. Data aggregation is the process of summarising and combining sensor data to reduce the amount of data that needs to be sent across the network. Sensor nodes can be attacked in different ways because wireless sensor networks are often used to send private information in dangerous and remote places. One of these is the "packet drop attack," in which the sensor nodes that have been hacked drop whole packets or just some of them on purpose. So, the algorithms for wireless sensor networks must be made with security in mind. This thesis presents the secure multi-path optimization based QoS Algorithm (SMO-QoS), which is a safe and energy-aware routing algorithm that uses the Lion optimisation algorithm LOA. The network is split into groups based on k-means grouping to save energy and make it easy to combine data. SMO-QoS looks at key factors like packet drop, residual node energy, linked node density, average cluster distance, and average transmission delay to figure out how fit the network is. LOA's suggested multi-target function is used to figure out the best route. Simulation results showed that safe data aggregation and energy use were both much better than with the existing systems.