Autonomous, failure-resilient orchestration of distributed discrete event simulations

Abstract

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 associated with the simulation. To manage these processing requirements in a scalable manner, a discrete event simulation 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 property not only complicates the orchestration of the discrete event simulation in a distributed setting, but also makes providing reliable, fault-tolerant execution a challenge, especially when compared to conventional distributed fault tolerance schemes.In this paper, we propose an autonomous agent that provides fault tolerance functionality for discrete event simulations 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 production discrete event simulation that can sustain failures while running under the supervision of our fault tolerance framework.

Predictive analytics using statistical, learning, and ensemble methods to support real-time exploration of discrete event simulations

“…Each modification of the input parameters requires a new set of iterations to be run. Dividing the target simulation into several units and executing them in parallel is one way to improve overall execution times [5,6], but generally does not enable real-time exploration. In this work, we target real-time computational guarantees that involve providing subsecond, interactive responses to the user as simulation parameters are changed.…”

Autonomous Orchestration of Distributed Discrete Event Simulations in the Presence of Resource Uncertainty

“…Authors' addresses: Z. Sui, M. Malensek, andS. Pallickara, Computer Science Department, Colorado State University, 1873 Campus Delivery, Fort Collins, CO 80523-1873, USA; Harvey, Department of Computing and Information Science, University of Guelph, Guelph, Ontario N1G 2W1, Canada.…”

“…Ultimately, each of these items can have severe and unexpected performance consequences in a distributed setting and must be accounted for to ensure that resources are used efficiently. Our prior research [Malensek et al 2013], which focused on autonomous fault tolerance functionality, has been extended in this article to target the two remaining aspects of resource uncertainty. Resource slowdowns may occur due to an increase in the number of processes executing concurrently at the resource, load spikes, or runaway processes resulting from a coding error.…”