Multiprocessor resource allocation for hard-real-time streaming with a dynamic job-mix

Abstract

An embedded multiprocessor that can run multiple hard-real-time (HRT) jobs simultaneously has to guarantee that enough resources are available to meet the timing constraints. It is essential that both application model and hardware be tailored to this goal. Moreover, suitable resource allocation and scheduling are needed. This paper proposes a resource allocator that gives guarantees for HRT streaming applications. Because new jobs arrive during operation, resource allocation is performed at run-time. This provides admission control. Resource budget enforcement is handled by local schedulers. We formalize our resource allocation problem and show that it is NP-complete. We developed heuristics to tackle the problem during runtime and evaluated them. A modified First-fit Vector Bin-Packing algorithm provides a good solution; it can allocate 95% of the resources, while handling a large number of job arrivals and departures on a heavily loaded system.