Garbage Collector Scheduling in Dynamic, Multiprocessor Real-Time Systems

We consider garbage collection (GC) in dynamic, multiprocessor real-time systems. We consider the time-based, concurrent GC approach and focus on real-time scheduling to obtain mutator timing assurances, despite memory allocation and garbage collection. We present a scheduling algorithm called GCMUA. The algorithm considers mutator activities that are subject to time/utility function time constraints, stochastic execution-time and memory demands, and overloads. We establish that GCMUA probabilistically lower bounds each mutator activity's accrued utility, lower bounds the system-wide total accrued utility, and upper bounds the timing assurances' sensitivity to variations in mutator execution-time and memory demand estimates. Our simulation experiments validate our analytical results and confirm GCMUA's effectiveness.