Multiple processes may contend for shared resources such as variables stored in the shared memory of a multiprocessor system. Mechanisms required to preserve data consistency on such systems often lead to a decrease in system performance. This research focuses on scheduling policies that control shared resource contention and achieve high capacity and scalability in multiprocessor-based applications that include telephone switches and real-time databases. Based on analytic models three different scheduling approaches are analyzed.