  Recently, elevated LiDAR (ELiD) has been proposed as an alternative to local
LiDAR sensors in autonomous vehicles (AV) because of the ability to reduce
costs and computational requirements of AVs, reduce the number of overlapping
sensors mapping an area, and to allow for a multiplicity of LiDAR sensing
applications with the same shared LiDAR map data. Since ELiDs have been removed
from the vehicle, their data must be processed externally in the cloud or on
the edge, necessitating an optimized backhaul system that allocates data
efficiently to compute servers. In this paper, we address this need for an
optimized backhaul system by formulating a mixed-integer programming problem
that minimizes the average latency of the uplink and downlink hop-by-hop
transmission plus computation time for each ELiD while considering different
bandwidth allocation schemes. We show that our model is capable of allocating
resources for differing topologies, and we perform a sensitivity analysis that
demonstrates the robustness of our problem formulation under different
circumstances.
