  The ongoing research and industrial exploitation of SDN and NFV technologies
promise higher flexibility on network automation and infrastructure
optimization. Choosing the location of Virtual Network Functions is a central
problem in the automation and optimization of the software-defined,
virtualization-based next generation of networks such as 5G and beyond. Network
services provided for autonomous vehicles, factory automation, e-health and
cloud robotics often require strict delay bounds and reliability constraints,
which are influenced by the location of its composing Virtual Network
Functions. Robots, vehicles and other end-devices provide significant
capabilities such as actuators, sensors and local computation which are
essential for some services. Moreover, these devices are continuously on the
move and might lose network connection or run out of battery power, which
further challenge service delivery in this dynamic environment. This work
tackles the mobility, and battery restrictions; as well as the temporal aspects
and conflicting traits of reliable, low latency service deployment over a
volatile network, where mobile compute nodes act as an extension of the cloud
and edge computing infrastructure. The problem is formulated as a
cost-minimizing Virtual Network Function placement optimization and an
efficient heuristic is proposed. The algorithms are extensively evaluated from
various aspects by simulation on detailed real-world scenarios.
