Investigating global behavior in computing grids

Abstract. We investigate effects of spoofing attacks on the scheduling and execution of basic application workflows in a moderately loaded grid computing system using a simulation model based on 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. To understand the resulting global behavior, we adapt multidimensional analyses as a measurement approach for analysis of complex information systems. We use this approach to show that the surprising performance fall-off 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.