Second, we jointly optimize computation and communication task scheduling for streaming applications on MPSoCs with the objective of minimizing schedule length by totally removing intercore communication overhead. By minimizing schedule length, the system performance can be improved by adopting a smaller period or exploring the slacks generated for energy reduction with DVS. To guarantee the schedulability of communication tasks, we perform the schedulability analysis, and theoretically obtain the upper bound of the times needed to reschedule each computation task. Based on the analysis, we formulate the scheduling problem as an ILP (Integer Linear Programming) formulation and obtain an optimal solution. Experimental results show that our technique can achieve a 27.72% reduction in schedule length and a 14.98% reduction in energy consumption compared with previous work. Third, we study the problem of removing intercore communication overhead for streaming applications on MPSoCs with the objective of minimizing the overall memory usage. The intercore communication overhead not only impacts time performance considerably but also influences the total memory usage of MPSoC architecture. Our basic idea is to let tasks with intra-period data dependencies transform to inter-period data dependencies so as to totally remove the intercore communication overhead. To solve the problem, we first perform analysis and obtain the bounds of the times needed to reschedule each task. Then we formulate the scheduling problem as an ILP model to obtain an optimal schedule. We also propose a heuristic approach to efficiently obtain a near optimal solution. Experimental results show that the proposed approach can significantly reduce the schedule length and improve the memory usage compared with previous work.