  Vehicle-to-everything (V2X) services are attracting a lot of attention in the
research and industry communities due to their applicability in the landscape
of connected and autonomous vehicles. Such applications have stringent
performance requirements in terms of complex data processing and low latency
communications which are utilized to ensure road safety and improve road
conditions. To address these challenges, the placement of V2X applications
through leveraging of edge computing paradigm, that distributes the computing
capabilities to access points in proximity to the vehicles, presents itself as
a viable solution. However, the realistic implementation of the edge enabled
V2X applications is hindered by the limited computational power provided at the
edge and the nature of V2X applications that are composed of multiple
independent V2X basic services. To address these challenges, this work targets
the efficient placement of V2X basic services in a highway scenario subject to
the delay constraints of V2X applications using them and the limited
computational resources at the edge. To that end, this work formulates a binary
integer linear programming model that minimizes the delay of V2X applications
while satisfying the resource requirements of V2X basic services. To
demonstrate the soundness of the approach, simulations with varying vehicle
densities were conducted, and the results reported show that it can satisfy the
delay requirements of V2X applications.
