Modeling and Simulation of Load Balancing Strategies for Computing in High Energy Physics

Abstract

The amount of data to be processed by experiments in high energy physics (HEP) will increase tremendously in the coming years. To cope with this increasing load, most efficient usage of the resources is mandatory. Furthermore, the computing resources for user jobs in HEP will be increasingly distributed and heterogeneous, resulting in more difficult scheduling due to the increasing complexity of the system. We aim to create a simulation for the WLCG helping the HEP community to solve both challenges: a more efficient utilization of the grid and coping with the rising complexity of the system. There is currently no simulation in existence which helps the operators of the grid to make the correct decisions while optimizing the load balancing strategy. This paper presents a proof of concept in which the computing jobs at the Tier 1 center GridKa are modeled and simulated. To model the computing jobs we extended the Palladio simulator with a mechanism to simulate load balancing strategies. Furthermore, we implemented an automated model parameter analysis and model creation. Finally, the simulation results are validated using real-word performance data. Our results suggest that simulating larger parts of the grid is feasible and can help to optimize the utilization of the grid.