An adaptive join-the-biased-queue rule for load sharing on distributed computer systems

An adaptive version of the join-the-biased-queue rule, originally proposed for the assignment of jobs to a simple parallel system of queues, is presented. The adaptive algorithm provides the foundation for an adaptive load sharing routine for a class of Unix multiprocessor systems. The authors utilize a combination of the available instantaneous information about the number of processes active on each processor and periodically collected average CPU run-queue-length information as an index of load to aid in assigning processes to the various processors for execution. Their algorithm aims at maintaining the system in an operating condition characterized by a balance in the normalized average CPU run-queue-lengths observed by the various processors, even when the offered workload has unknown and time-varying characteristics. The bias components in the join-the-biased-queue rule are periodically recalculated by using a simple stochastic approximation procedure. The load sharing strategy consistently deals with the constraints imposed by the nature of the considered systems and their workload, such as overheads and implementation costs, nonhomogeneities, measurement errors, and nonmigration. Extensive simulation studies of the algorithm behavior, together with laboratory measurements on the algorithm implementation for the AT&T 3B4000 computer system, confirm the superior performance, stability, and robustness of the algorithm. The approach can be applied in the solution of load sharing or routing problems in more general contexts than the one considered