Contention Cognizant Scheduling of Task Graphs on Shared Bus-Based Heterogeneous Platforms

Demands for high performance as well as reliability within stringent resource budgets are driving a shift from homogeneous to heterogeneous processing platforms for the implementation of today’s cyber-physical systems (CPSs). These CPSs are typically represented as directed-acyclic task graphs (DTGs) due to the complex interactions between their functional components which are often distributed in nature. This work deals with the problem of scheduling a CPS modeled as DTG. First, we present an optimal solution using integer linear programming (ILP) for the DTGs, to be executed on distributed heterogeneous processors which are interconnected via shared buses. However, this ILP-based optimal solution exhibits high computational complexity and does not scale for moderately large problem sizes. Hence, we propose a low-overhead heuristic algorithm called the contention cognizant task and message scheduler (CC-TMS), which is able to produce satisfactorily efficient as well as fast solutions within a reasonable time. The efficiency of the proposed scheme has been extensively evaluated through simulation-based experiments using benchmark DTGs. Through the case study of a real-world automotive traction controller, we demonstrate the practical applicability of our proposed scheme.