Parameter-Based Clustering Algorithm for Clustered Wireless Sensor Networks with High Altitude Platforms as the Base Station
Dimas Aji Pangestu, Hendrawan Hendrawan, Iskandar Iskandar · 2021
Wireless sensor network (WSN) is predicted to become an important part of life, perhaps surpassing today's personal computers. This prediction arises because various uses of WSN can be applied in various fields. However, there are constraints on energy limitations in WSN so that a mechanism is needed so it can increase the efficiency of energy use in WSN. What can be done to contribute further to WSN development and overcome the problems faced is to create an algorithm that can regulate how all sensors work in the network. This paper presents a clustering algorithm that uses three clustering parameters, they are α, β, and γ, each of which plays a role in parameter weighting in terms of remaining energy, distance, and cluster capacity, respectively. This algorithm is applied to clustered wireless sensor networks with High Altitude Platforms (HAPS) as the base station. This algorithm helps to increase in data collection and transfer, thereby saving energy. The performance of the proposed clustering algorithm is evaluated through several simulations based on lifetime.