Research On The UAV Based Data Collection Method In Wireless Sensor Network

Data collection is the most fundamental task in WSN (wireless senor network:WSN). However, the main data collection methods in WSN have faced great challenges in dealing with "the energy hole problem", "the constrained moving ablility of the sink" and "the limited application scenarios". Thus, they are unable to provide a long-term and effective data collection service for the WSN.To solve the problems above mentioned, we use the UAV (unmanned aerial vehicle:UAV) based data collection method, which is the latest data collection method in WSN. However, the energy of the ordinary UAV is limited in the real-world environment, which makes it impossible for the UAV to collect the whole data generated by the network. Faced with this challenge, we propose a UAV data collection method based on some data-critical nodes that can represent all the nodes under the application error range. Using this method, the UAV can collect the most valuable data in the network under limited energy. In summary, the specific research works of this paper are as follows:1) The method to find the data-critical nodes in the WSN:Faced with the problem of losing data, caused by the limited energy of the UAV, we start with the data value and find out a few critical nodes, named as data-critical nodes in this thesis, according to the similarity among different nodes. These nodes have great data value and the data sensed by them can represent all the nodes in WSN. We choose them as the data collection targets of the UAV. By modelling the problem to a selection optimization problem and proving it's a NP-hard problem, we design an algorithm based on the greedy strategy. The time complexity of the algorithm is O(n~2).2) The path planning method that guides the UAV to collect data:There is a critical problem: how to schedule the UAV's path to make it works more effectively while it only has limited energy? To solve this problem, we model it to a selection optimization problem and prove it's a NPC problem. Then we propose a heuristic algorithm, which takes the unexpected abnormal data sensed by the nodes and the possibility of meeting obstacles by UAV into consideration during the data collection process, and ensures that the data collected by the UAV has maximal value. The time complexity of this algorithm is O(n~2).