Autonomous, Failure-resilient Orchestration of Distributed Discrete Event Simulations

Discrete event simulations model the behavior of complex, real-world systems. Simulating a wide range of relevant events and conditions naturally provides a more accurate model, but also increases the computational workload as-sociated with the simulation. To manage these processing requirements in a scalable manner, a discrete event sim-ulation can be distributed across a number of computing resources. However, individual tasks in the simulation are stateful, and therefore require inter-task communication and synchronization to produce an accurate model. This prop-erty not only complicates the orchestration of the discrete event simulation in a distributed setting, but also makes providing reliable, fault-tolerant execution a challenge, es-pecially when compared to conventional distributed fault tolerance schemes. In this paper, we propose an autonomous agent that pro-vides fault tolerance functionality for discrete event simu-lations by predicting state changes in the simulation and adjusting its fault tolerance policy accordingly. This allows the system to avoid negatively impacting overall execution times while preserving reliability guarantees. To underscore the viability of our solution, we provide benchmarks of a pro-duction discrete event simulation that can sustain failures while running under the supervision of our fault tolerance framework