4.8 Article

UAV-Driven Sustainable and Quality-Aware Data Collection in Robotic Wireless Sensor Networks

Journal

IEEE INTERNET OF THINGS JOURNAL
Volume 9, Issue 24, Pages 25150-25164

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2022.3195677

Keywords

Cluster-based routing; energy-efficient routing; Internet of Things (IoT); robotic network; unmanned aerial vehicle (UAV); wireless sensor network (WSN)

Funding

  1. Natural Sciencesand Engineering Research Council of Canada (NSERC)

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Energy-aware data collection is crucial for robotic and wireless sensor networks. UAV-aided approaches can reduce energy consumption, but the battery capacity of the UAV needs to be considered.
Energy-aware data collection is of paramount importance for robotic and wireless sensor networks. Although static sink-aided cluster-based protocols provide energy-efficient solutions, unmanned aerial vehicle (UAV)-aided approaches can be considered as better alternatives to reduce energy consumption while data acquisition compared with static sinks. Most of the existing UAV-driven solutions have not considered a limit on the battery capacity of the UAV, which needs to be considered in a practical manner. This article investigates energy-aware data collection in robot network clusters. In each cluster, a cluster head (CH) robot allocates one collaborative task to each cluster member (CM) robot and collects data from CMs whereas a UAV collects data from CH robots by visiting a subset of them due to its battery limitation. To complement the state-of-the-art, UAV decision for visiting the subset of CHs is constrained to multiple factors including residual battery capacity, as well as locations and data qualities of all CH robots. Nonvisited CH robots use CH robots as relay nodes for data forwarding. Following upon this, by considering the problem under data hopping constraints, this article also presents a sensitivity analysis with respect to data hopping constraints. Simulations show that the proposed policy achieves zero total joint cost whereas the state-of-the-art approaches result in significantly high total joint costs. Furthermore, the proposed policy reduces the total joint cost by up to 50% with respect to the conventional approaches.

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