Hard Real-time Hybrid Garbage Collection with Low Memory Requirements

Current real-time garbage collection algorithms are usually criticised for their high memory requirements. Even when consuming nearly 50% of CPU time, some garbage collectors ask for at least twice the memory as really needed. This paper explores the fundamental reason for this problem and proposes a new performance indicator for the evaluation of real-time garbage collection algorithms. Use of this performance indicator motivates an algorithm that combines both reference counting and mark-and-sweep techniques. In the presence of our collector, a garbage collected hard real-time system can achieve the correct balance of time-space tradeoff with less effort. In order to provide both temporal and spatial guarantees needed by a hard real-time application, an offline analysis is developed and integrated into the current response time analysis framework. Moreover, the use of dual priority scheduling of the garbage collection tasks allows spare capacity in the system to be reclaimed whilst guaranteeing deadlines.