4.7 Article Proceedings Paper

Flight Time Minimization of UAV for Data Collection Over Wireless Sensor Networks

Journal

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
Volume 36, Issue 9, Pages 1942-1954

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSAC.2018.2864420

Keywords

Unmanned aerial vehicles (UAVs); wireless sensor networks; trajectory optimization; dynamic programming

Funding

  1. NSFC [61771495, 61725101, 61501527, 61501024, 61731018]
  2. Science and Technology Program of Guangzhou [201707010166]
  3. Shenzhen Fundamental Research Fund [KQTD2015033114415450]
  4. State's Key Project of Research and Development Plan [2016YFE0122900-3]
  5. Science, Technology and Innovation Commission of Shenzhen Municipality [JCYJ20170816151823313]
  6. Guangdong Science and Technology Project [2016B010126003]
  7. Beijing NSF [L172020]
  8. Fundamental Research Funds for the Central Universities

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In this paper, we consider a scenario where an unmanned aerial vehicle (UAV) collects data from a set of sensors on a straight line. The UAV can either cruise or hover while communicating with the sensors. The objective is to minimize the UAV's total flight time from a starting point to a destination while allowing each sensor to successfully upload a certain amount of data using a given amount of energy. The whole trajectory is divided into non-overlapping data collection intervals, in each of which one sensor is served by the UAV. The data collection intervals, the UAV's speed, and the sensors' transmit powers are jointly optimized. The formulated flight time minimization problem is difficult to solve. We first show that when only one sensor is present, the sensor's transmit power follows a water-filling policy and the UAV's speed can be found efficiently by bisection search. Then, we show that for the general case with multiple sensors, the flight time minimization problem can be equivalently reformulated as a dynamic programming (DP) problem. The subproblem involved in each stage of the DP reduces to handle the case with only one sensor node. Numerical results present the insightful behaviors of the UAV and the sensors. Specifically, it is observed that the UAV's optimal speed is proportional to the given energy of the sensors and the intersensor distance, but it is inversely proportional to the data upload requirement.

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