On optimal strategies for cycle-stealing in networks of workstations

We study the parallel scheduling problem for a new modality of parallel computing: having one workstation "steal cycles" from another. We focus on a draconian mode of cycle-stealing, in which the owner of workstation B allows workstation A to take control of B's processor whenever it is idle, with the promise of relinquishing control immediately upon demand. The typically high communication overhead for supplying workstation B with work and receiving its results militates in favor of supplying B with large amounts of work at a time; the risk of losing work in progress when the owner of B reclaims the workstation militates in favor of supplying B with a sequence of small packets of work. The challenge is to balance these two pressures in a way that maximizes the amount of work accomplished. We formulate two models of cycle-stealing. The first attempts to maximize the expected work accomplished during a single episode, when one knows the probability distribution of the return of B's owner. The second attempts to match the productivity of an omniscient cycle-stealer, when one knows how much work that stealer can accomplish. We derive optimal scheduling strategies for sample scenarios within each of these models.