Result: Multi-scale analysis of large distributed computing systems

Large scale distributed systems are composed of many thousands of computing units. Today's examples of such systems are grid, volunteer and cloud computing platforms. Generally, their analyses are done through monitoring tools that gather resource information like processor or network utilization, providing high-level statistics and basic resource usage traces. Such approaches are recognized as rather scalable but are unfortunately often insufficient to detect or fully understand unexpected behavior. In this paper, we investigate the use of more detailed tracing techniques --commonly used in parallel computing-- in distributed systems. Finely analyzing the behavior of such systems comprising thousands of resources over several months may seem infeasible. Yet, we show that the resulting trace can be analyzed using tools that enable to easily zoom in and out on selected area of space and time. We use the BOINC volunteer computing system as a basis of this study. Since detailed activity traces of the BOINC clients are not available yet, we rely instead on traces obtained through a BOINC simulator developed with the SimGrid toolkit and which uses as input real availability trace files from the Seti@Home BOINC project. We show that the analysis of such detailed resource utilization traces provides several non-trivial insights about the whole system and enables the discovery of unexpected behavior.