Evaluating the performance of demultiplexing strategies for real-time CORBA

Efficient and predictable demultiplexing is necessary to provide real-time support for distributed object computing applications developed with CORBA. This paper presents two contributions to the study of demultiplexing for real-time CORBA endsystems. First, we present an empirical study of four CORBA request demultiplexing strategies (linear search, perfect hashing, dynamic hashing, and active demultiplexing) for a range of target objects and operations. Second, we describe our use of the perfect hashing and active demultiplexing strategies to develop a high-performance, real-time object request broker (ORB) called TAO.