Length-based blocking and local estimations in distributed simulation: a case study

2002 ◽  
Author(s):  
C.D. Pham ◽  
S. Fdida
Keyword(s):  
Distributed Simulation

Containerization of high level architecture-based simulations: A case study

2016 ◽  
Vol 14 (2) ◽  
pp. 115-138 ◽  
Author(s):  
Tom van den Berg ◽  
Barry Siegel ◽  
Anthony Cramp
Keyword(s):  
Cloud Computing ◽  
Distributed Simulation ◽  
Background Information ◽  
Service Orientation ◽  
High Level Architecture ◽  
Recent Emergence ◽  
High Level ◽  
Acquisition Processes ◽  
Simulation Environments

NATO and the nations use distributed simulation environments for various purposes, such as training, mission rehearsal, and decision support in acquisition processes. Consequently, modeling and simulation (M&S) has become a critical technology for the coalition and its nations. Achieving interoperability between participating simulation systems and ensuring credibility of results currently often requires enormous effort with regards to time, personnel, and budget. Recent technical developments in the area of cloud computing technology and service oriented architecture (SOA) may offer opportunities to better utilize M&S capabilities in order to satisfy NATO critical needs. A new concept that includes service orientation and the provision of M&S applications via the as-a-service model of cloud computing may enable composable simulation environments that can be deployed rapidly and on-demand. This new concept is known as M&S as a Service (MSaaS). There has also been the recent emergence of containerization as an alternative to virtualization. Containerization is the process of creating, packaging, distributing, deploying, and executing applications in a lightweight and standardized process execution environment known as a container. Because containers are, in principle, lightweight, they are suitable to serve as the vehicle for the provision of packaged (micro)services. Service orientation is an approach to the design of heterogeneous, distributed systems in which solution logic is structured in the form of interoperating services. This paper investigates various aspects of service orientation and containerization including simulation composition, networking, discovery, scalability, and overall performance. This investigation provides background information on the topics of service orientation, containerization, and Docker – a technology ecosystem for working with containers. A case study is presented for the use of Docker in support of a training simulation based on the high level architecture (HLA). The HLA is an IEEE standard architecture for distributed simulation environments that was originally developed for defense applications. The case study introduces a number of training use cases, and shows how Docker can be used to assist in their implementation. The performance impact of running a simulation within container technology is also investigated. The application of container technology to HLA-based simulations as presented in this paper is novel. The motivation for looking at this topic stems from the activity being conducted within NATO MSG-136.

A case study of verification, validation, and accreditation for advanced distributed simulation

1997 ◽  
Vol 7 (3) ◽  
pp. 393-424 ◽  
Author(s):  
Ernest H. Page ◽  
Bradford S. Canova ◽  
John A. Tufarolo
Keyword(s):  
Distributed Simulation

scholarly journals Distributed Simulation with Multi-Agents for IoT in a Retail Pharmacy Facility

Information ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 527
Author(s):  
Mohammed Basingab
Keyword(s):  
Distributed System ◽  
Distributed Simulation ◽  
Economic Feasibility ◽  
Retail Chain ◽  
Simulation Paradigm ◽  
Geographically Distributed ◽  
Iot Devices ◽  
Future Technologies ◽  
Multi Agents

Nowadays, internet of things (IoT) technology is considered as one of the key future technologies. The adoption of such technology is receiving quick attention from many industries as competitive pressures inspire them to move forward and invest. As technologies continue to advance, such as IoT, there is a vital need for an approach to identify its viability. This research proposes the adoption of IoT technology and the use of a simulation paradigm to capture the complexity of a system, offer reliable and continuous perceptions into its present and likely future state, and evaluate the economic feasibility of such adoption. A case study of one of the largest pharmacy retail chain is presented. IoT devices are suggested to be used to remotely monitor the failures of a geographically distributed system of refrigeration units. Multi-agents distributed system is proposed to simulate the operational behavior of the refrigerators and calculate the return of investment (ROI) of the proposed IoT implementation.

Symposium on Distributed Simulation for Military Training of Teams/Groups: A Case Study of Distributed Training and Training Performance

1995 ◽  
Vol 39 (20) ◽  
pp. 1316-1320 ◽  
Author(s):  
Daniel J. Dwyer ◽  
Randall L. Oser ◽  
Jennifer E. Fowlkes
Keyword(s):  
Distributed Simulation ◽  
Military Training ◽  
Training Environment ◽  
Training Performance ◽  
Distributed Training ◽  
Actual Application ◽  
Measurement Tools ◽  
The Military ◽  
Measuring Training

This paper describes the first actual application of a distributed training network to the military mission called Close Air Support (CAS). It represents a “case study” and is based upon a set of data collected on military personnel during a one-week series of exercises in a distributed training environment. We describe the objectives of the measurement process, discuss the development and use of the measurement tools, provide several observations based upon the data collected, and offer several preliminary conclusions related to measuring training performance in distributed environments.

Distributed simulation of coloured Petri Nets: A case study using distributed caches

2016 ◽  
Author(s):  
Cornell G. F. Junior ◽  
L. C. Marques Vasconcelos ◽  
G. C. Barroso ◽  
J. M. Soares ◽  
L. F. Leite
Keyword(s):  
Petri Nets ◽  
Distributed Simulation ◽  
Coloured Petri Nets
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