Complex real time systems need databases to support concurrent data access and provide well defined interfaces between software modules. However, conventional database systems and prior real time database systems do not provide the performance or predictability needed by high speed, hard real time applications. The authors designed, implemented, and evaluated an object oriented database system called MDARTS (Multiprocessor Database Architecture for Real Time Systems). MDARTS avoids the client server overhead of most prior real time database systems and object oriented, real time systems by moving transaction execution into application tasks. By eliminating these sources of overhead and focusing on basic data management services for control systems (data sharing, serializable transactions, and multiprocessor support), the MDARTS prototype provides hard real time transaction times approximately three orders of magnitude faster than prior real time database systems. MDARTS ensures bounded locking delay by disabling preemption when a transaction is waiting for a lock, and hence, allows for the estimation of worst case transaction execution times. Another contribution of MDARTS is that it supports explicit declarations of real time requirements and semantic constraints within application code. The MDARTS library examines these declarations at application initialization time and attempts to construct objects that are compatible with the requirements. Besides local shared memory transactions with hard real time response time guarantees, MDARTS also supports remote transactions that use remote procedure calls for data access with less stringent timing constraints. The MDARTS prototype is implemented in C++ and it runs on VME based multiprocessors and Sun workstations.

Prior work on real time scheduling with global shared resources in multiprocessor systems assigns as much blocking as possible to the lowest priority tasks. We show that better schedulability can be achieved if global blocking is distributed according to the blocking tolerance of tasks rather than their execution priorities. We describe an algorithm that assigns global semaphore queue priorities according to blocking tolerance, and we present simulation results demonstrating the advantages of this approach with rate monotonic scheduling. Our simulations also show that a simple FIFO usually provides better real time schedulability with global semaphores than priority queues that use task execution priorities.>

For performance reasons, client applications often need to influence the implementation strategies of libraries whose services they use. If an object-oriented library contains multiple service classes customized for different usage patterns, applications can influence service implementations by instantiating the customized classes that match their needs. However, with many similar service classes, it can be difficult for applications to determine which classes to instantiate. Choosing the wrong class can result in very subtle errors since a customized class might use optimizations that work only over a restricted domain. In this paper, we show how client-side software contracts and exemplar-based class factories can be used to construct customized server objects. By expressing priorities and requirements in contracts, clients can delegate service class selection to the library and thereby avoid implicit dependencies on the library implementation. We have used this approach in the implementation of a real-time database system.