MEC-Enabled Fine-Grained Task Offloading for UAV Networks in Urban Environments

In recent years, with the continuous development of information technology, amount data generated and hosted by cloud service platforms in urban environments is unprecedented. Mobile edge computing (MEC) combined UAV networks to better realize ability provide nearby services a large number terminal devices cities. Unmanned aerial vehicles (UAVs) are highly maneuverable inexpensive good carriers for carrying MEC platforms. networks, we usually face problem fine-grained task offloading based on relevant features environments. We need address high energy consumption processing delays help achieve sustainability goals. Therefore, combine software definition network (SDN) technology and, this basis, propose two strategies an improved EFO intelligent algorithm different user scales. At same time, run proposed system sensor. The experiment shows that, compared traditional strategy, unloading efficiency method can be about 10%.