Bridging the gap: a standards-based approach to OR/MS distributed simulation
Taylor, Simon J.E.
Turner, Stephen J.
ACM Trans. Model. Comput. Simul.
Association for Computing Machinery
In Operations Research and Management Science (OR/MS), Discrete Event Simulation (DES) models are typically created using commercial simulation packages such as Simul8™ and SLX™. A DES model represents the processes associated with a system of interest; but, in cases where the underlying system is large and/or logically divided, the system may be conceptualized as several sub-systems. These sub-systems may belong to multiple stakeholders, and creating an all-encompassing DES model may be difficult for reasons such as, concerns among the intra- and inter-organizational stakeholders with regard to data/information sharing (e.g., security and privacy). Furthermore, issues such as model composability, data transfer/access problems and execution speed may also make a single model approach problematic. A potential solution could be to create/reuse well-defined DES models, each modeling the processes associated with one sub-system, and using distributed simulation technique to execute the models as a unified whole. Although this approach holds great promise, there are technical barriers. One such barrier is the lack of common ground between distributed simulation developers and simulation practitioners. In an attempt to bridge this gap, this paper reports on the outcome of an international standardization effort, the SISO-STD-006-2010 Standard for Commercial-Off-The-Shelf Simulation Package Interoperability References Models (IRMs). This facilitates the capture of interoperability requirements at a modeling level rather than a technical level and enables simulation practitioners and vendors to properly specify the interoperability requirements of a distributed simulation in their terms. Two distributed simulation examples are given to illustrate the use of IRMs.
Pre-print version. Final version published in ACM Transactions on Modeling and Computer Simulation (TOMACS); available online at http://tomacs.acm.org/
Vol. 22, pp. 18 - 18