This paper presents an executable model of grid computing systems and a measurement approach, based on multidimensional analysis, to understand global behavior in a complex system. Specifically, we investigate effects of spoofing attacks on the scheduling and execution of jobs with basic application workflows in a moderately loaded grid that models standard specifications. We conduct experiments to first subject this grid to spoofing attacks that reduce resource availability and increase relative load. A reasonable change in client behavior is then introduced to counter the attack, which unexpectedly causes global performance degradation. Using multidimensional analyses, we show that this surprising result occurs because the change in client behavior causes a rearrangement of the global job execution schedule in which completion times inadvertently increase. Finally, we argue that viewing distributed resource allocation as a self-organizing process improves understanding of behavior in distributed systems such as computing grids.
1st International Conference on Self-Organizing Systems