This survey examines the sources, propagation mechanisms, and observable impacts of timing variability in microservice-based systems, using software-defined vehicles as a motivating example, and compares major classes of timing models by their assumptions about workload stability, execution structure, resource sharing, observability, and guarantee admissibility.
Abstract
Microservice-based systems are modular and adaptable, but their distributed structure makes their timing behavior difficult to analyze and guarantee. Because latency emerges from interactions among service dependencies, shared resources, and coordinating middleware, local timing disturbances can propagate into system-level effects. This survey examines the sources, propagation mechanisms, and observable impacts of timing variability in microservice-based systems, using software-defined vehicles as a motivating example. It compares major classes of timing models by their assumptions about workload stability, execution structure, resource sharing, observability, and guarantee admissibility, and summarizes their limitations within microservice-based software-defined vehicles.
A formal verification framework that consists of a combination of specifications of temporal logic, model checking and modeling of service interactions graphs to study the behavior of the system and confirm the correctness properties is suggested.
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