Energy Efficient Data Forwarding in Disconnected Networks Using Cooperative UAVs

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Almasoud, Abdullah
Selim, Mohamed
Alqasir, Abdullah
Shabnam, Tanzilah
Masadeh, Ala'eddin
Kamal, Ahmed
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Electrical and Computer Engineering

Data forwarding from a source to a sink node when they are not within the communication range is a challenging problem in wireless networking. With the increasing demand of wireless networks, several applications have emerged where a group of users are disconnected from their targeted destinations. Therefore, we consider in this paper a multi-Unmanned Aerial Vehicles (UAVs) system to convey collected data from isolated fields to the base station. In each field, a group of sensors or Internet of Things devices are distributed and send their data to one UAV. The UAVs collaborate in forwarding the collected data to the base station in order to maximize the minimum battery level for all UAVs by the end of the service time. Hence, a group of UAVs can meet at a waypoint along their path to the base station such that one UAV collects the data from all other UAVs and moves forward to another meeting point or the base station. All other UAVs that relayed their messages return back to their initial locations. All collected data from all fields reach to the base station within a certain maximum time to guarantee a certain quality of service. We formulate the problem as a Mixed Integer Nonlinear Program (MINLP), then we reformulated the problem as Mixed Integer Linear Program (MILP) after we linearize the mathematical model. Simulations results show the advantages of adopting the proposed model in using the UAVs' energy more efficiently.


This is a manuscript of a proceeding published as Almasoud, Abdullah M., Mohamed Y. Selim, Abdullah Alqasir, Tanzilah Shabnam, Alaeddin Masadeh, and Ahmed E. Kamal. "Energy efficient data forwarding in disconnected networks using cooperative UAVs." In 2018 IEEE Global Communications Conference (GLOBECOM). DOI: 10.1109/GLOCOM.2018.8647594. Posted with permission.

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Mon Jan 01 00:00:00 UTC 2018