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, 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 load balancing. The middleware services have been implemented and employed for (1) the DynBench dynamic real-time benchmark suite and (2) an experimental Navy system. Experimental results show the effectiveness of our load balancing techniques for consistently delivering real-time quality-of-service, even in highly dynamic environments.
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