Hummingbird: An UAV-aided Energy E cient Algorithm for Data Gathering in Wireless Sensor Networks

• Other Authors: Papa, Rafael (author)
• Format: Others
• Language: English
• Published: Florida Atlantic University
• Subjects: Wireless sensor networks > Energy conservation.; Wireless sensor nodes.; Drone aircraft.
• Online Access: http://purl.flvc.org/fau/fd/FA00013093

Energy e ciency is a critical constraint in wireless sensor networks. Wireless sensor networks (WSNs) consist of a large number of battery-powered sensor nodes, connected to each other and equipped with low-power transmission radios. Usually, the sensor nodes closer to the sink are more likely to become overloaded and subject to draining their battery faster than the nodes farther away, creating a funneling e ect. The use of a mobile device as a sink node to perform data gathering is a well known solution to balance the energy consumption in the entire network. To address this problem, in this work we consider the use of an UAV as a mobile sink. An unmanned aircraft vehicle (UAV) is an aircraft without a human pilot on-board, popularly known as a Drone. In this thesis, besides the use of the UAV as a mobile sink node, we propose an UAV-aided algorithm for data gathering in wireless sensor networks, called Humming- bird. Our distributed algorithm is energy-e cient. Rather than using an arbitrary path, the UAV implements an approximation algorithm to solve the well-known NP- Hard problem, the Traveling Salesman Problem (or TSP), to setup the trajectory of node points to visit for data gathering. In our approach, both the path planning and the data gathering are performed by the UAV, and this is seamlessly integrated with sensor data reporting. The results, using ns-3 network simulator show that our algorithm improves the network lifetime compared to regular (non-UAV) data gathering, especially for data intensive applications. === Includes bibliography. === Thesis (M.S.)--Florida Atlantic University, 2018. === FAU Electronic Theses and Dissertations Collection