# Scheduling the Exchange of Context Information for Time-Triggered Adaptive Systems
## 2 Related Work
### Adaptation in Time-Triggered Systems
The approach consists of a monitor used to monitor the resources within the MCNoC and reconfigure them based on a priori recovery strategies. The work in [18] does not consider the timing requirement of the context information exchanged between resources in cooperation with the global schedule. Conceptualizing context information along with its respective timing requirements enables the scheduling of context information only when needed. In our approach, the resource utilization needed for communicating context information is minimized by factoring in the timing requirement of the context communication. An adaptive time-triggered multi-core architecture (ATMA) is developed in [9]. The proposed ATMA extends beyond adaptation by leveraging WCET while also addressing failure events and changing environmental conditions. The work describes an architecture that utilizes a network-on-chip (NoC), multi-schedule graphs, and building blocks such as context agreement units, context monitors, and adaptation units. The approach is based on mapping a unique schedule to the different system states. The schedules of the processing elements and NoC are switched at runtime to adapt to various scenarios. Inconsistency in the global view for schedule changes is avoided using the context monitor and agreement unit, thanks to the distributed approach for adaptation decision-making in ATMA. Adaptive control methods have also been investigated for enhancing fault tolerance in nonlinear systems. In [19], an adaptive critic-based fault-tolerant control (FTC) strategy is proposed using approximate dynamic programming for systems with unknown dynamics and asymmetric constrained inputs. The approach formulates the FTC problem as a zero-sum game and uses an actor-critic neural network structure to approximate optimal control policies. While this strategy supports online adaptation and ensures convergence under certain assumptions, it does not offer deterministic guarantees on timing or resource usage, nor does it support coordinated adaptation across distributed components. In contrast, our approach integrates fault tolerance within a time-triggered metascheduling framework, ensuring predictable context propagation and bounded resource usage under fault conditions. While the works mentioned above explore different strategies for enabling adaptation in time-triggered systems, including fault tolerance and learning-based control, they often overlook the communication and resource overhead associated with propagating context information. In particular, the exchange of context between processing elements is usually treated as an external process or assumed to be constantly active, resulting in excessive communication, increased power consumption, and reduced scalability. In contrast, our approach integrates context exchange directly into the scheduling problem by embedding it within the metascheduling framework, allowing for the selective triggering of context propagation only for the relevant processing elements. It minimizes the overhead and ensures that adaptation remains efficient, predictable, and resource-aware.