Feedback coupled resource allocation policies in the multiprogramming-multiprocessor computer system
Model studies of some integrated, feedback-driven scheduling systems for multiprogrammed-multiprocessor computer systems are presented. The basic control variables used are the data-flow rates for the processes executing on the CPU. The model systems feature simulated continuous-flow and preempt-resume scheduling of input-output activity. Attention is given to the amount of memory resource required for effective processing of the I/O activity (buffer space assignment). The model studies used both distribution-driven and trace-driven techniques. Even relatively simple dynamic schedulers are shown to improve system performance (as measured by user CPU time) over that given by optimal or near-optimal static schedulers imbedded in identical system structures and workload environments. The improvement is greatest under a heavy I/O demand workload.