Improving performance of optimistic simulation for distributed simulation system using speculative computation

Simulation is aimed very often to solve problems of great complexity requiring – beyond using the advanced simulation software tools – platforms that enable the implementation of such software systems. In recent years the concept of cloud computing has emerged and is being applied more and more widely for solving such problems. This paper, beyond delineating the main trends of the development of distributed simulation over a grid, especially over the Internet through Web-based applications, highlights the concepts of service-based simulation system approach. This concept gives the possibility of implementing Web- or cloud agents and other ASP system compliant simulation services based on simulation standards. As a sample application, Fuzzy Web Service is demonstrated as a part of CASSANDRA 4.0 (Cognizant Adaptive Simulation System for Applications in Numerous Different Relevant Areas) that is developed by the McLeod Institute of Simulation Sciences Hungarian Center.

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A unified distributed simulation system

1990 Winter Simulation Conference Proceedings ◽

10.1109/wsc.1990.129553 ◽

2002 ◽

Cited By ~ 5

Author(s):

J. McAffer

Keyword(s):

Distributed Simulation ◽

Simulation System

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Multiple Resolution Modeling: A Particular Case of Distributed Simulation

Information ◽

10.3390/info11100469 ◽

2020 ◽

Vol 11 (10) ◽

pp. 469

Author(s):

Mario Marin ◽

Gene Lee ◽

Jaeho Kim

Keyword(s):

Distributed Simulation ◽

Research Area ◽

Simulation System ◽

Lessons Learned ◽

Point Of View ◽

High Level Architecture ◽

Unique Form ◽

The Future ◽

New Research ◽

High Level

Multiple resolution modeling (MRM) is the future of distributed simulation. This article describes different definitions and notions related to MRM. MRM is a relatively new research area, and there is a demand for simulator integration from a modeling complexity point of view. This article also analyzes a taxonomy based on the experience of the researchers in detail. Finally, an example that uses the high-level architecture (HLA) is explained to illustrate the above definitions and, in particular, to look at the problems that are common to these distributed simulation configurations. The steps required to build an MRM distributed simulation system are introduced. The conclusions describe the lessons learned for this unique form of distributed simulation.

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Framework of Distributed Simulation System for Multi-agent Environment

PRICAI 2000 Topics in Artificial Intelligence - Lecture Notes in Computer Science ◽

10.1007/3-540-44533-1_100 ◽

2000 ◽

pp. 811-811

Author(s):

Itsuki Noda

Keyword(s):

Distributed Simulation ◽

Simulation System ◽

Multi Agent

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On the Use of Controlled Types for Fossil Collection in a Distributed Simulation System

Reliable Software Technologies — Ada-Europe’ 99 - Lecture Notes in Computer Science ◽

10.1007/3-540-48753-0_21 ◽

1999 ◽

pp. 238-249

Author(s):

Helge Hagenauer

Keyword(s):

Distributed Simulation ◽

Simulation System

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A System for Data Processing on Supply-Chain Distributed Simulation Platform Based on Agent

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.26-28.397 ◽

2010 ◽

Vol 26-28 ◽

pp. 397-400 ◽

Cited By ~ 1

Author(s):

Zhi Xun Sun ◽

Jie Lin

Keyword(s):

Decision Making ◽

Supply Chain ◽

Data Storage ◽

Distributed Simulation ◽

Simulation System ◽

Simulation Platform ◽

Simulation Performance ◽

Dynamic Display ◽

Time Simulation ◽

Supply Chain Simulation

To deal with the result data of the supply-chain simulation, such as data storage, analysis and display, a data system based on agent has been developed. Utilize agent’s intelligence and interaction; realize the dynamic display of the real-time simulation status and statistics analysis. The simulation performance can then be viewed and analyzed to provide the decision making. The system, as an indispensible part of the simulation platform, supports the simulation system effectively.

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