Abstract:
An unmanned aerial vehicle (UAV)-assisted wireless network collects data from ground sensor nodes (SN) and transfers it to a depot. Age of information (AoI) and UAV energy consumption are performance metrics.
Most importantly, decreasing the AoI requires the UAV to return to the depot more often, increasing energy consumption. To reveal the Pareto frontier, we design UAV paths that optimize these two competing metrics jointly.
This problem is formulated using a multi-objective mixed integer linear programming (MILP) with a flow-based constraint set and Bender’s decomposition. The proposed method yields non-dominated solutions when designing the UAV path.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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