SIDLE: Semantically Intelligent Distributed Leader Election Algorithm for Wireless Sensor Networks

TL;DR

This paper presents SIDLE, a semantically intelligent distributed leader election algorithm designed for heterogeneous wireless sensor networks in IoT applications, optimizing energy use and data aggregation.

Contribution

The paper introduces SIDLE, a novel leader election algorithm that enhances energy efficiency and data processing in heterogeneous WSANs for IoT deployments.

Findings

Improved energy efficiency in sensor networks.

Enhanced data aggregation and global zone view.

Effective deployment in rural IoT scenarios.

Abstract

This paper introduces the deployment of a group of Wireless Sensor and Actuator Network (WSAN) for Internet of Thing (IoT) systems in rural regions deployed by a drone dropping sensors and actuators at a certain position as a mesh of a hexagonal form. Nodes are heterogeneous in hardware and functionality thus not all nodes are able to transfer data directly to the base station. Primitive ones are only capable of collecting local data. However, ones that are more sophisticated are equipped with long-range radio telemetry and more computational power. Power optimization is one of the crucial factors in designing WSANs. Total power consumption must be minimized, as sensors are self-managed. It is not feasible to collect sensors on time bases and recharge the batteries. Therefore, energy consumption optimization and harvesting green energy are other factors that are considered. In this regard, protocols are designed in a way to support such requirements. The preprocessed data are first collected and combined by the leaders at each hexagonal cell. Then, the information packets are sent to the head clusters. Consequently, head clusters reprocess the received information and depict a better global view of the zone, using a variety of the received information. Finally, the processed information is sent to the nearest base station or a mobile drone.