Abstract
The recent technological evolution of drones along with the constantly growing maturity of its commercialization, has led to the emergence of novel drone-based applications within the field of wireless sensor networks for information collection purposes. In such settings, especially when deployed in outdoor environments with limited external control, energy consumption and robustness are challenging problems for the system’s operation. In the present paper, a drone-assisted wireless sensor network is studied, the aim being to coordinate the routing of information (among the ground nodes and its propagation to the drone), investigating several drone trajectories or route shapes and examining their impact on information collection (the aim being to minimize transmissions and consequently, energy consumption). The main contribution lies on the proposed algorithms that coordinate the communication between (terrestrial) sensor nodes and the drone that may follow different route shapes. It is shown through simulations using soft random geometric graphs that the number of transmitted messages for each drone route shape depends on the rotational symmetry around the center of each shape. An interesting result is that the higher the order of symmetry, the lower the number of transmitted messages for data collection. Contrary, for those cases that the order of symmetry is the same, even for different route shapes, similar number of messages is transmitted. In addition to the simulation results, an experimental demonstration, using spatial data from grit bin locations, further validates the proposed solution under real-world conditions, demonstrating the applicability of the proposed approach.
Highlights
Modern network systems are characterized by large volumes of data that call for novel and more efficient methods to gather, process, disseminate, etc. the acquired information
The growth of the technologies related to unmanned aerial vehicles, most commonly known as drones, has led to their consideration as potential assets in the direction of enhancing the dynamics of Internet of Things (IoT) and WSNs [4], especially due to their broad availability and continuously decreased cost
Optimization techniques, like those based on Travelling Salesman Problem (TSP) variants, are considered when it comes to solving the route planning problem for data collection through means such as drones and mobile sinks [13,16,53,55,57,58,59,60]
Summary
Modern network systems are characterized by large volumes of data that call for novel and more efficient methods to gather, process, disseminate, etc. the acquired information. The growth of the technologies related to unmanned aerial vehicles, most commonly known as drones, has led to their consideration as potential assets in the direction of enhancing the dynamics of Internet of Things (IoT) and WSNs [4], especially due to their broad availability and continuously decreased cost This is, valid for 5G mobile infrastructures [5], where it is expected that reliable communication with efficient and effective connectivity for a massive number of devices, could benefit from the use of drone-based systems. The launch of (relatively) cheap and easy to deploy drones is expected to increase the dimensional space (by adding an extra degree of freedom) of a network, covering scenarios where aerial assistance may be vital This is evident in WSN environments, where metrics like the number of exchanged messages, distance, etc., are crucial for the system’s efficiency (e.g., reduced energy consumption and lifetime elongation).
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