Adaptive Time-Triggered Multi-Core Architecture

Abstract

The static resource allocation in time-triggered systems offers significant benefits for the safety arguments of dependable systems. However, adaptation is a key factor for energy efficiency and fault recovery in Cyber-Physical System (CPS). This paper introduces the Adaptive Time-Triggered Multi-Core Architecture (ATMA), which supports adaptation using multi-schedule graphs while preserving the key properties of time-triggered systems including implicit synchronization, temporal predictability and avoidance of resource conflicts. ATMA is an overall architecture for safety-critical CPS based on a network-on-a-chip with building blocks for context agreement and adaptation. Context information is established in a globally consistent manner, providing the foundation for the temporally aligned switching of schedules in the network interfaces. A meta-scheduling algorithm computes schedule graphs and avoids state explosion with reconvergence horizons for events. For each tile, the relevant part of the schedule graph is efficiently stored using difference encodings and interpreted by the adaptation logic. The architecture was evaluated using an FPGA-based implementation and example scenarios employing adaptation for improved energy efficiency. The evaluation demonstrated the benefits of adaptation while showing the overhead and the trade-off between the degree of adaptation and the memory consumption for multi-schedule graphs.

Adaptive Scheduling for Time-Triggered Network-on-Chip-Based Multi-Core Architecture Using Genetic Algorithm

“…As the number of context events is increased from 0 to 10, MSG sizes increase exponentially. Existing metascheduling techniques [2,6] highlights this exponential growth of 2 n , where n is the number of context events considered. In [2], a reconvergence of paths in MSG is proposed but not evaluated.…”

“…Existing metascheduling techniques [2,6] highlights this exponential growth of 2 n , where n is the number of context events considered. In [2], a reconvergence of paths in MSG is proposed but not evaluated. However, this work extends the earlier work in [2] by implementing and evaluating the reconvergence of paths algorithm for a metascheduler.…”

“…In [2], a reconvergence of paths in MSG is proposed but not evaluated. However, this work extends the earlier work in [2] by implementing and evaluating the reconvergence of paths algorithm for a metascheduler. However, the size of the MSG is reduced in all six cases (Figures 5-10) as reconvergence of paths is applied.…”

“…Fault tolerance at a lower cost than active redundancy, energy efficiency, and adaptation to changing environmental conditions necessitates adaptation services to accommodate run-time changes. These run-time changes may arise from an execution slack (slack events), failures in system resources (failure events) or from a change in an operational mode requiring different application services [2]. These run time events are referred to in this work as context events.…”

“…The metascheduler pre-computes the MSG at design time using an application, platform and context model. A significant concern of the MSG is state-space explosion [2]. The exponential growth of the MSG caused by the increasing number of context events results in the state-space explosion.…”