A Benefit Accrual Model For Distributed Real-Time Computers

In distributed real-time computing systems, the laws of physics and the intrinsic nature of the applications are contrary to the premises which underlie most traditional real-time computing principles and technology. This necessitates a more general model of real-time which accommodates non-stochastically non-deterministic activities that nonetheless have mission-critical completion time constraints. Our model expresses result completion time constraints in terms of: the benefit to the system that the results yield, individually and collectively, as a function of their completion times (and other parameters); together with application-specific predicates for correctness optimization based on accruing benefit. To exploit this generality, we have devised experimental best-effort real-time scheduling algorithms which analysis, simulation, and measurement have shown to accrue higher benefit than do traditional algorithms, and which have the greater dynamic situational coverage required in distributed real-time computing systems.

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