Many real-time scheduling problems have been proven to be NP-hard. Recently (1996), we proposed a randomized optimization framework for efficiently solving such NP-hard problems. The proposed method, called the nested partitions (NP) method, is proved to converge to global optimal solutions and it is also highly matched to emerging massively parallel processing capabilities. In particular, we apply the NP method to solve the scheduling of real-time tasks with minimum jitter.
展开▼
