MERC: Energy-Efficient Multi-DAG Scheduling with Contention and Reliability Awareness on NoC-Based MPSoCs

Network-on-Chip (NoC)-based Multi-Processor Systems-on-Chip (MPSoCs) are increasingly required to execute multiple real-time applications simultaneously. Each application is modelled as a Directed Acyclic Graph (DAG) of dependent tasks, and the platform supports Dynamic Voltage and Frequency Scaling (DVFS). While existing task-mapping methods address energy efficiency, reliability, and network contention for a single DAG, they do not capture the inter-DAG contention that arises when communication flows from independent applications compete for shared NoC links, nor the cross-DAG resource sharing that forces tasks from different applications to be serialised on the same Processing Element (PE). In this paper, we formulate the multi-DAG contention- and reliability-aware task mapping problem as a Mixed-Integer Nonlinear Program (MINLP). To handle the quartic constraint growth that renders exact solvers impractical for realistic workloads, we propose MERC , a polynomial-time heuristic for the multi-DAG setting. MERC performs (i)  global task placement with cross-DAG load balancing and (ii)  joint V/F selection and edge scheduling via greedy list scheduling with worst-case contention slack, optionally followed by a contention refinement phase that computes precise inter-DAG slack and exploits recovered time for frequency reduction. Extensive simulations on random DAGs over 2 × 2 to 6 × 6 mesh topologies demonstrate that MERC provides the best multi-objective balance among all compared methods: 60% lower energy than round-robin placement, 10– \(56\% \) lower energy than an adapted multi-DTG heuristic (SAFLA-N), robust feasibility where independent single-DAG scheduling collapses at scale, and polynomial-time execution that is two orders of magnitude faster than a metaheuristic baseline. A cycle-accurate Noxim cross-check supports the reserved-path delay model under concurrent DAG traffic, and a case study of three edge applications confirms the same multi-objective reading.