영문내용
(English Abstract) |
Low Earth Orbit Satellites (LEOSats) and Unmanned Aerial Vehicles (UAVs) integrated network has become one promising solution for providing the ubiquitous communication and computing services to the resource-constrained ground IoT devices. However, it is challenging to optimally allocate the communication resources to the devices due to the existence of inter-cell interference. Moreover, owing to the limited energy budget and the computing resources, the task offloading needs to be optimally determined without incurring high execution delay for the devices and overloading the UAVs. Therefore, in this work, we propose a space-aerial-assisted multi-access edge computing system where the tasks of devices are partially executed at the UAVs and LEOSat in addition to local computing at the devices. Under the consideration of task execution deadline, we jointly allocate the resources and determine task offloading so that the energy consumption of devices and UAVs is minimized. To address the formulated mix-integer non-convex problem, the block successive upper-bound minimization (BSUM) method is exploited that can ensure to achieve the stationary points of the non-convex objective function. |
