Improving voronoi scoping with Ant Colony optimization Algorithm for efficient energy consumption in Multi-hop wireless sensor network of Tin mining

Abstract

The method of extracting tin from the earth is known as "tin mining." The tin seams' safety is still low, and they experience many deserters. Therefore, it is necessary to monitor the parameters like soil moisture, water level, temperature, PH, and methane gas on a regular basis in the underground tin mining tunnels. Because of the complexities of the tin mining tunnels and the variety of activities carried out in these mines, it is necessary to improve the existing monitoring system of these tunnels. Wireless sensor networks (WSN) are used in the monitoring of tin tunnels, however due to the tunnel environment that requires regular monitoring, and due to energy constraints in WSN, this reduces the network lifetime. This study proposes an Energy Efficient Algorithm for Multi-Hop Wireless Sensor Network (EEA-MHWSN) of an IoT safety system for increasing its network lifetime and real-time monitoring. This IoT system is composed of master and slave controllers that are interconnected to form a wireless sensor network. Slave controllers sense threats in the tunnel and send stimuli to the master controller. As there are many master controllers, they form a network called Multi-Hop WSN. The reading in this tin tunnel are parameters like soil moisture, dangerous gas, temperature, and humidity. As the above IoT devices communicate via Wi-Fi, they consume a lot of energy. For improving that energy consumption of these IoT devices in tunnels, this study proposed nodes clustering, where each cluster is represented by a cluster header, this happen by applying (EEA-MHWSN), which is an improvement of the Voronoi scoping algorithm functionality, where in EEA-MHWSN there is use of anti-colony optimization algorithm which is associated to each cluster header for optimizing their energy consumption. Their heuristic has been studied and shown through simulation, and its efficiency has been compared with that of the Multilink distributed power control algorithm (MSDPC-SRMS) [5]. Where EEA-MHWSN is more efficient than MSDPCSRMS.