We evaluate pathchar , a tool that infers the characteristics of links along an Internet path (latency, bandwidth, queue delays). Looking at two example paths, we identify circumstances where pathchar is likely to succeed, and develop techniques to improve the accuracy of pathchar 's estimates and reduce the time it takes to generate them. The most successful of these techniques is a form of adaptive data collection that reduces the number of measurements pathchar needs by more than 90% for some links.

We consider policies for CPU load balancing in networks of workstations. We address the question of whether preemptive migration (migrating active processes) is necessary, or whether remote execution (migrating processes only at the time of birth) is sufficient for load balancing. We show that resolving this issue is strongly tied to understanding the process lifetime distribution. Our measurements indicate that the distribution of lifetimes for a UNIX process is Pareto (heavy-tailed), with a consistent functional form over a variety of workloads. We show how to apply this distribution to derive a preemptive migration policy that requires no hand-tuned parameters. We used a trace-driven simulation to show that our preemptive migration strategy is far more effective than remote execution, even when the memory transfer cost is high.

We consider policies for CPU load balancing in networks of workstations. We address the question of whether preemptive migration (migrating active processes) is necessary, or whether remote execution (migrating processes only at the time of birth) is sufficient for load balancing. We show that resolving this issue is strongly tied to understanding the process lifetime distribution. Our measurements indicate that the distribution of lifetimes for a UNIX process is Pareto (heavy-tailed), with a consistent functional form over a variety of workloads. We show how to apply this distribution to derive a preemptive migration policy that requires no hand-tuned parameters. We used a trace-driven simulation to show that our preemptive migration strategy is far more effective than remote execution, even when the memory transfer cost is high.

We present statistical techniques forpredicting the queue times experienced by jobs submitted to a space-sharing parallel machine with jrst-come-jrst-served (FCFS) scheduling. We apply these techniques to trace data from the Intel Paragon at the San Diego Supercomputer Center and the IBM SP2 at the Cornell Theory Centel: We show that it is possible to predict queue times with accuracy that is acceptable f o r several intended applications. The coeficient of correlation between our predicted queue times and the actual queue times from simulated schedules is between 0.65 and 0.12.