Title
Data farming in support of HLA performance assessment
Author
Cramp, A.J.
van den Berg, T.W.
Huiskamp, W.
Publication year
2014
Abstract
Performance assessment is a key factor in designing distributed simulation environments that are fit-forpurpose and cost-effective. Simulations used for training applications should provide the required level of responsiveness and interactivity. Simulations used for analysis or decision support should execute as fast as possible to enable quick results on large numbers of scenarios and variables. There are many parameters that have an impact on the performance of a typical High Level Architecture (HLA) federation. We describe a structured process for using data farming (experiment design, simulation, cloud computing, and data mining) in order to identify key parameters affecting the performance of HLA federations. A parameterized and instrumented federation is designed with parameters covering areas suspected of impacting HLA performance and instrumentation measuring key values of HLA performance. One key parameter set for HLA performance is the computing platform that hosts the federation. Varying such a platform in an efficient and cost effective manner is possible using cloud computing via Infrastructure-as-a- Service providers. Finally, the performance measures captured during federation execution are collated and analysed using data mining techniques to identify key parameters and their effect on the performance of the federation. By including the Runtime Infrastructure (RTI) as a parameter in the federation design, it may also be possible to identify where the HLA itself (instead of particular RTIs or computing platforms) is impacting on simulation performance. Initial results from this process are presented and future work, including the creation of a HLA performance model from identified parameters, is discussed.
Subject
Operations Modelling
MSG - Modelling Simulation & Gaming
ELSS - Earth, Life and Social Sciences
Defence Research
Simulation
Defence, Safety and Security
Cloud computing
Cost effectiveness
Data mining
Decision support systems
Distributed simulation environments
High level architecture
Identified parameter
Performance assessment
Performance measure
Run-time infrastructure
Simulation performance
Training applications
Parameter estimation
To reference this document use:
http://resolver.tudelft.nl/uuid:d6649f80-4d34-43b3-941a-619e627f9e4a
TNO identifier
520167
Publisher
SISO, Orlando, FL
Source
2014 Fall Simulation Interoperability Workshops (SIW), 8-12 September 2014, Orlando, Florida, USA, 317-328
Article number
14F-SIW-047
Document type
conference paper