Techniques for Optimizing CORBA Middleware for Distributed Embedded Systems

This paper appeared in the proceedings of IEEE INFOCOM ’99, New York, New York, March 21–25th, 1999. Abstract—The distributed embedded systems industry is poised to leverage emerging real-time operating systems, such as Inferno, Windows CE, EPOC, and Palm OS to support mobile communication applications, such as electronic mail, Internet browsing, and network management. Ideally, these applications can be developed using standard middleware components like CORBA to improve their quality and reduce their cost and cycle time. However, stringent constraints on memory available in embedded systems imposes a severe limit on the footprint of CORBA middleware. This paper provides three contributions to the study and design of small footprint, embedded CORBA middleware. First, we describe the optimizations used to develop the protocol engine and CORBA IDL compiler provided by TAO, which is our real-time CORBA implementation. TAO’s IDL compiler produces stubs that can use either compiled and/or interpretive marshaling. Second, we compare the performance and footprint of TAO IDL compiler-generated stubs and skeletons that use compiled and/or interpretive marshaling for a wide range of IDL data types. Third, we illustrate the benefits of the small footprint and efficiency of TAO IDL compilergenerated stubs and skeletons for CORBA Object Services implemented using TAO. Our results comparing the performance of the compiled and interpretive stubs and skeletons indicate that the interpretive stubs and skeletons perform between 75-100% of the compiled stubs and skeletons for a wide range of data types. However, the code size for the interpreted stubs and skeletons was between 26-45% and 50-80% of the compiled stubs and skeletons, respectively. These results indicate a positive step towards implementing high performance, small footprint middleware for distributed embedded systems. Keywords—Communication protocols and software, Real-time CORBA, minimal ORB footprint, performance, hand-held devices.