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-Real-time optimization of the overall performance of a large computer system or network such as an air-traffic control system or teleprocessing network inherently requires the introduction of adaptive control into selected control functions or sets of control functions. Such adaptive control is necessitated by the high variance of the available resource inventory and the workload resource demands within the system environment. Global management of the resulting multiloop control system becomes the responsibility of the operating system. Investigated aspects of this evolutionary extension of the operating system called the dynamically adaptive operating system (DAOS) include the general methodology and the real-time modeling and estimation of resource demands. The methodology specifies the general identification, decision, and modification processes required for an adaptive operating system. Support of such processes could be attractively provided by a peripheral or miniprocessor. The problem of estimating resource service times both with and without partial service times is explored and statistical models possessing utility for real-time modeling are developed. In particular, a dynamically partitioned second moment model (DPSMM) is described. The feasibility of such models is established with respect to a General Principle of Locality. Selected simulation results are presented to evaluate selected developments with respect to an adaptive central processing unit (CPU) scheduling discipline.