Adaptive Task Allocation for Multiprocessor SoCs in Real-Time Energy Harvesting Systems

Tongquan Wei1,  Yonghe Guo2,  Xiaodao Chen2,  Shiyan Hu2
1Computer Science and Technology department, East China Normal University, 2Electrical and Computer Engineering department, Michigan Technological University


This paper proposes an adaptive energy efficient task allocation scheme for a multiprocessor system-on-a-chip (SoC) in real-time energy harvesting systems. The proposed scheme generates an energy efficient offline task schedule for a multiprocessor SoC energy harvesting system by balancing application workload among multiple processing elements and pushing real-time application towards their deadlines. The offline task schedule is dynamically extended to adapt to the energy availability in the runtime to improve the probability of a task to be feasibly scheduled. Simulation experiments show that the proposed scheme achieves energy savings of up to 24%, and reduces task deadline miss ratio of up to 10%.