Some classes of real-time systems function in environments which cannot be modeled with static approaches. In such environments, the arrival rates of events which drive transient computations may be unknown. Also, the periodic computations may be required to process varying numbers of data elements per period, but the number of data elements to be processed in an arbitrary period cannot be known at the time of system engineering, nor can an upper bound be determined for the number of data items; thus, a worst case execution time cannot be obtained for such periodics. This paper presents middleware services that support such dynamic real-time systems through adaptive resource management. The middleware services have been implemented and employed for components of the experimental Navy system described by L.R. Welch et al. (1996). Experimental characterizations show that the services provide timely responses, that they have a low degree of intrusiveness on hardware resources, and that they are scalable.
['Lonnie R. Welch', 'Binoy Ravindran', 'P.V. Werne', 'Michael W. Masters', 'Behrooz Shirazi', 'Prashant A. Shirolkar', 'Robert Harrison', 'W. Mills', 'Tuy Do', 'Joseph LaFratta', 'Shafqat Anwar', 'S. Sharp', 'T. Sergeant', 'G. Bilowus', 'M. Swick', 'J. Hoppel', 'J. Caruso']
Distributed, scalable, dependable real-time systems: middleware services and applications