Mobility-Aware Real-Time Task Allocation in the 5G-Enabled Embedded-Edge Compute Continuum

Cyber-physical systems are getting increasingly connected to cellular and wireless networks. As a prominent example, the automotive industry has witnessed a rapid increase in embedded software and electronics, and lately also increased connectivity to cellular communication networks. This trend enables the deployment of applications on network edge computers, offering opportunities for reduced embedded hardware footprint and increased expandability of new applications. Put differently, the traditional automotive platform comprising embedded networked processors expands to the cellular network and edge computing services in its environment. For real-time applications, which are very common in the automotive domain, the aforementioned trend gives rise to completely new challenges in that mobility and the underlying cellular network impact the temporal properties and the design and implementation decisions of the application. In this paper, we address the problem of synthesizing task allocation of real-time applications in the embedded-edge compute continuum, with key considerations for mobility and minimization of embedded compute utilization. We present an exact SMT-based solution as well as efficient heuristics with extensive experimental evaluations.