Adaptation of System Dynamics Model Execution Algorithms for Cloud-based Environment

This paper presents a process of adaptation of system dynamics models execution algorithms to cloud-based environment. System dynamics is an aspect of systems theory as a method to understand the dynamic behaviour of complex systems. Existing modeling algorithms used in popular modeling solutions are either not available for free use or have several disadvantages which prevent them from being used in distributed cloud environment. Adaptation of execution algorithms aimed not only to adapt execution process to distributed parallel environments with higher reliability and wider range of possible applications, but also to improve system dynamics model execution performance. For example, existing algorithms of model execution which are not ready for distributed environments will fail to complete modeling task in case of hardware failure, and optimized ones are able to smoothly transfer execution process from one node to another with minimal impact on overall model execution progress. Such capabilities help to save many resources and, especially, time on execution re-runs. In this paper described algorithms and approaches designed for sdCloud solution which are focused on transferring execution of system dynamics models into distributed cloud-based environment and shown extra benefits brought to modeling process by shift to the cloud.