The available capacity of a privately owned workstation environment

Abstract

Powerful workstations interconnected by networks have become widely available as sources of computing cycles. Each workstation is typically owned by a single user in order to provide a high quality of service for the owner. In most cases, an owner does not have computing demands as large as the capacity of the workstation. Therefore, most of the workstations are underutilized. Nevertheless, some users have demands that exceed the capacities of their workstations. In order to effectively share the capacity of workstations, there must be algorithms that allocate available capacity and long periods when owners do not use their stations. To understand the profile of station availability, we analyzed the usage patterns of a cluster of workstations. The workstations were available more than 75% of the time observed. Large capacities were steadily available on an hour to hour, day to day, and month to month basis. These capacities were available not only during the evening hours and on weekends, but during the busiest times of normal working hours. A stochastic model was developed which was based on an analysis of the relative frequency distribution and the correlation of available and non-available interval lengths. A 3-stage hyperexponential cumulative distribution has been fitted to the observed cumulative relative frequency of available periods. The fitted distribution closely matches the observed relative frequency distribution. This stochastic model is important as a workload generator for the performance evaluation of capacity sharing strategies of a cluster of workstations. The model assists in the design of resource management algorithms that take advantage of the characteristics of the usage patterns.