AI summaryⓘ
The authors explain that the Computing Continuum connects computing resources from the edge (like your phone or local devices) to the cloud to improve how services work. However, because these resources are varied and always changing, managing services across them is complicated. They suggest using ideas from brain science, called Active Inference, to help services adapt on their own by understanding their environment. The authors also point out that current solutions don't fully solve this problem and emphasize the need for shared tools to test and compare different management methods. Their work outlines future research needed to make service management in the Computing Continuum more reliable and scalable.
Computing ContinuumEdge ComputingCloud ComputingService OrchestrationActive InferenceSelf-organizing SystemsSimulation EnvironmentsService QualityHeterogeneous Infrastructure
Authors
Boris Sedlak, Víctor Casamayor Pujol, Ildefons Magrans de Abril, Praveen Kumar Donta, Adel N. Toosi, Schahram Dustdar
Abstract
The Computing Continuum (CC) integrates different layers of processing infrastructure, from Edge to Cloud, to optimize service quality through ubiquitous and reliable computation. Compared to central architectures, however, heterogeneous and dynamic infrastructure increases the complexity for service orchestration. To guide research, this article first summarizes structural problems of the CC, and then, envisions an ideal solution for autonomous service orchestration across the CC. As one instantiation, we show how Active Inference, a concept from neuroscience, can support self-organizing services in continuously interpreting their environment to optimize service quality. Still, we conclude that no existing solution achieves our vision, but that research on service orchestration faces several structural challenges. Most notably: provide standardized simulation and evaluation environments for comparing the performance of orchestration mechanisms. Together, the challenges outline a research roadmap toward resilient and scalable service orchestration in the CC.