  The transformation of smart mobility is unprecedented--Autonomous, shared and
electric connected vehicles, along with the urgent need to meet ambitious
net-zero targets by shifting to low-carbon transport modalities result in new
traffic patterns and requirements for real-time computation at large-scale, for
instance, augmented reality applications. The cloud computing paradigm can
neither respond to such low-latency requirements nor adapt resource allocation
to such dynamic spatio-temporal service requests. This paper addresses this
grand challenge by introducing a novel decentralized optimization framework for
mobility-aware edge-to-cloud resource allocation, service offloading,
provisioning and load-balancing. In contrast to related work, this framework
comes with superior efficiency and cost-effectiveness under evaluation in
real-world traffic settings and mobility datasets. This breakthrough capability
of 'computing follows vehicles' proves able to reduce utilization variance by
more than 40 times, while preventing service deadline violations by 14%-34%.
