Energy-Efficient Cluster-Based Data Collection by a UAV with a Limited-Capacity Battery in Robotic Wireless Sensor Networks

Abstract

In this work, our motivation focuses on an energy-efficient data collection problem by a mobile sink, an unmanned aerial vehicle (UAV) with limited battery capacity, in a robot network divided into several robot clusters. In each cluster, a cluster head (CH) robot allocates tasks to the remaining robots and collects data from them. Our contribution is to minimize the UAV total energy consumption coupled to minimum cost data collection from CH robots by visiting optimally a portion of the CH robots. The UAV decides the subset of CH robots to visit by considering not only the locations of all CH robots but also its battery capacity. If the UAV cannot visit all CH robots, then the CH robots not visited by the UAV transmit their data to another CH robot to forward it. The decision of transmission paths of transmitting robots is included in the cost optimization. Our contribution passes beyond the existing paradigms in the literature by considering the constant battery capacity for the UAV. We derive the optimal approach analytically for this problem. For various numbers of clusters, the performance of our strategy is compared with the approach in the close literature in terms of total energy consumed by CH robots, which affects network lifetime. Numerical results demonstrate that our strategy outperforms the approach in the close literature.

Optimal Cluster Head Selection in WSN with Convolutional Neural Network-Based Energy Level Prediction

“…In 2020, Gul et al [32] incorporated visiting an optimal number of CH robots while minimizing the total energy consumption of the UAV and the cost of data collection from CH robots. The UAV determines which subset of CH robots to visit by taking into account both its battery capacity and the locations of all CH robots.…”

“…The cluster head selection is used in [31]; the advantage is that the cost is reduced, and the drawback is that it needs to consider the scalability analysis. Finally, cluster head selection is deployed in [32]; the major benefit is that energy consumption is reduced, and the drawback is that consistency is not maintained.…”

SF-Partition-Based Clustering and Relaying Scheme for Resolving Near–Far Unfairness in IoT Multihop LoRa Networks

“…As a result, several studies based on clustering algorithms have been proposed for IoT LoRa networks. In [ 29 ], the authors proposed a two-stage energy-efficient cluster-based solution for data collection by a mobile sink in a robot network by considering the first stage as a travelling salesman problem and the second stage as the removal of some CH robots from the path to reduce the UAV’s energy consumption. In [ 30 ], the cluster-based layering approach for uplink multihop communication was analysed.…”

Robust Control Based on Adaptive Neural Network for the Process of Steady Formation of Continuous Contact Force in Unmanned Aerial Manipulator

“…In recent years, Unmanned Aerial Vehicles (UAVs) have been developing toward miniaturization and intelligence, as a kind of aerial robot. In particular, due to their Vertical Take-Off and Landing (VTOL) and hovering capabilities, multi-rotor UAVs have been used in many military or civil fields, such as photography [ 1 ], mapping [ 2 ], agriculture [ 3 , 4 ], inspection [ 5 ], monitoring [ 6 , 7 ], and data collection [ 8 , 9 ]. However, these applications are utilized for observation and perception, which have no direct contact with the surrounding environment.…”