# Scheduling the Exchange of Context Information for Time-Triggered Adaptive Systems
## 1 Introduction  
Time-triggered architectures are suitable for safety-critical applications in domains such as aerospace and automotive, where they help reduce power consumption, weight, and certification costs. Time-triggered systems such as time-sensitive networking (TSN) [1] and TTEthernet [2] offer deterministic communication mechanisms that fulfill stringent real-time and safety requirements. They allow mixed-criticality applications to coexist on a unified network infrastructure, which reduces the need for physically separated communication lines and dedicated processing units, leading to significant savings in wiring mass, component footprint, and energy usage, which are especially critical in aerospace systems. For example, TTEthernet has been deployed in platforms such as the Airbus A350 and NASA's Orion spacecraft to support reliable and predictable communication for flightcontrol, navigation, and actuation systems [3; 4]. In the automotive domain, time-triggered architectures are increasingly applied in Advanced Driver Assistance Systems (ADAS) [5], braking, and powertrain control, enabling consolidation of functionalities across fewer electronic control units (ECUs) and thus reducing both weight and power demands. Moreover, the temporal and spatial partitioning of tasks in time-triggered systems enhances fault containment. It contributes to efficient certification under industry safety standards, such as DO-178C for avionics and ISO 26262 for automotive systems [6]. Time-triggered architectures support precise worst-case timing analysis by avoiding dynamic arbitration and ensuring predictable timing, simplifying safety verification, and reducing certification overhead. These benefits have motivated the adoption of time-triggered paradigms in distributed embedded systems, where reliable and analyzable communication between spatially separated nodes is essential [7; 8], besides ensuring predictable and analyzable communication between processing elements. In such systems, time-triggered networks enable synchronized task execution and deterministic message delivery across multiple computing units, thereby improving composability and fault containment. As a result, time-triggered communication is increasingly deployed in the design of high-assurance, performance-constrained distributed systems operating in safety-critical domains [9]. In safety-critical systems, adaptation services are motivated by changing user-defined modes, environmental, energy, and failure scenarios. Resource allocation in time-triggered systems is carried out at design time, which promotes the safety argument for dependable systems. However, static resource allocation in time-triggered systems limits the adaptation to changing environment scenarios, failure scenarios, and power conditions during run-time. For this reason, metaschedulers are used to enable adaptation in time-triggered systems. The metascheduler is an offline tool that enables adaptation in a time-triggered system. The computed schedules can also include task remapping. When the analysis and mapping calculations are predicted at the design for different scenarios, it is called static remapping [10]. In some literature, metascheduling is also referred to as quasi-static [11] or hybrid scheduling [12], where task migration decisions are made based on an analysis performed at design time. Due to safety concerns, reconfiguring safety-critical systems is often restricted to selecting system-wide modes from statically defined scheduling tables (meta-tables) that prescribe the permitted behavior of system components. Metascheduling in distributed systems requires all participating entities--such as end systems and switches--to maintain a consistent view of context events so that transitions between schedule tables occur in a coordinated and deterministic manner, necessitating a reliable mechanism for exchanging system state information among these entities.