Evaluating flight coordination approaches of UAV squads for WSN data collection enhancing the internet range on WSN data collection

Abstract

Wireless sensor networks (WSNs) are an important means of collecting data in a variety of situations, such as the monitoring of large or hazardous areas. The retrieval of WSN data can yield better results through the use of unmanned aerial vehicles (UAVs), for example, concerning the increase in the amount of data collected and the decrease in the time between the collection and use of the data. In particular, disaster areas may be left without communication resources and with high residual risk to humans, at which point a WSN can be quickly launched by air to collect relevant data until other measures can be established. The set of rules of each problem's component (e.g., number of UAVs, UAVs dislocation control, sensors, communication) is considered the approaches to solve the problem. In this meaning, some studies present approaches for the use of UAVs for the collection of WSN data, focusing primarily on optimizing the path to be covered by a single UAV and relying on long-range communication that is always available; these studies do not explore the possibility of using several UAVs or the limitations on the range of communication. This work describes DADCA, a distributed scalable approach capable of coordinating groups of UAVs in WSN data collection with restricted communication range and without the use of optimization techniques. The results reveal that the amount of data collected by DADCA is similar or superior to path optimization approaches by up to 1%. In our proposed approach, the delay in receiving sensor messages is up to 46% shorter than in other approaches, and the required processing onboard UAVs can reach less than 75% of those using optimization-based algorithms. The results indicate that the DADCA can match and even surpass other presented approaches, since the path optimization is not a focus, while also incorporating the advantages of a distributed approach.

Data collection in IoT networks: Architecture, solutions, protocols and challenges

“…In ref. [81], the authors proposed a solution that describes DADCA, a scalable distributed approach capable of coordinating groups of drones in WSN data collection with a restricted communication range and without using optimisation techniques. Experimental results reveal that the amount of data collected by DADCA is similar or better than path optimisation approaches up to 1%.…”

Hybrid LoRa-IEEE 802.11s Opportunistic Mesh Networking for Flexible UAV Swarming

“…Ground-connected UAVs could act as swarm coordinators, communicating with the other swarm UAV new-mission instructions (e.g., new positions to reach or be maintained). Moreover, the proposed mesh networking scheme could simply be used to keep track of the UAV's positions in order to provide the control center with an updated overview of the swarm topology [94]. The control center, in turn, could send to the coordinators-and, then, to specific UAVs-the information needed to restore the desired swarm formation.…”