A Hybrid Adaptive Strategy for Task Allocation and Scheduling for Multi-applications on NoC-based Multicore Systems with Resource Sharing

International audienceAllocation and scheduling of applications affect the timing response and system performance, particularly for Network-on-Chip (NoC) based multicore systems executing realtime applications. These systems with multitasking processors provide improved opportunity for parallel application execution. In dynamic scenarios, runtime task allocation improves the system resource utilization and adapts to varying application workload. In this work, we present an efficient hybrid strategy for unified allocation and scheduling of tasks at runtime. By considering multitasking capability of processors, communication cost and task timing characteristics, potential allocation solutions are obtained at design-time. These are adapted for dynamic mapping and scheduling of computation and communication workloads of real-time applications. Simulation results show that the proposed approach achieves 34.2% and 26% average reduction in network latency and communication cost of the allocated applications. Also, the deadline satisfaction of the tasks improves on average by 42.1% while reducing the allocation-time overhead by 32% when compared with existing techniques