Cloud-Based Modeling and Simulation: Distributed Simulation Analysis

This report delves into the realm of cloud-based modeling and simulation, with a specific emphasis on the distributed simulation layer. It introduces the concept of distributed simulation, highlighting its evolution from early developments to current applications on multiprocessor platforms. The report examines the methods employed in distributed simulation, including the use of LANs to connect machines and exploit geographically distributed resources. A key aspect discussed is the synchronization process, also known as time management, which is crucial for ensuring accurate results. The report also touches upon the importance of communication protocols and explores future research directions, particularly addressing the limitations found in applications and the significant changes in processing stages and programming. The report concludes with references to seminal works and current research in the field, emphasizing the ongoing relevance of distributed simulation.

CLOUD-BASED MODELING & SIMULATION
Introducing the distributed simulation layer
author name
affiliation
Abstract— The distributed simulation is exercised along with
the execution part of the simulation application that is being
computed on multiprocessor platform. The paper mainly aims on
the synchronous evaluation of the discrete simulation application.
This part of the simulation system has developed and remains in
the active part of the research until today. Some introduction of
the divided simulation is introduced that ranges from the seminal
work like the simultaneity to current work of execution of the
large-scale simulations on the super computers.Keywords—
modeling, simulation, performance, security, reliability, and
interoperability
I. INTRODUCTION
The distributed simulation part of the simulation was
introduced in the 1970s and 80s from various overlapping
communities. The distributive simulation community was
founded, developing during the research and the advancement
attempts of the defence community that always concentrated
on the interrelated developed simulations. This exploration in
the beginning concentrated on the simulations for the training
purpose, however tolerably extended to including regions, for
example, testing and examination and execution of physical
devices. As there are various contrasts between the PDES and
distributed simulations, there are also numerous identical
issues. Informally the distributive simulation is characterized
as the part that encloses the issues that are rising from both the
communities from the evaluation of single simulation
program.
II. METHODS
The Distributed Simulations are included along with the
assessment of the simulations are over the figuring stages that
is extended to a lot more extensive geographic degree than
that of parallel PCs. In contrast with the parallel simulations
where the simulation is executed inside the cabinet within the
automated room, the distributed simulation may be executed
on the arrangement of machines that are connected to one
another with the local area networks (LAN) [1]. The central
object of using the distributed simulation systems are allowed
to exploitations of geographically distributed resources.
The main issue in the primary part of motivation for
using the distributed simulation field, the want to add various
simulators performing on various computational techs into a
specific simulation environment. While the synchronization-
taking place is also known as time management in the
distributed simulation literature [2]. A great part of the
previous researches in distributed simulations concentrated on
conveying data among the test systems taking an interest in
the distributed simulation in an effective and appropriate
manner. [4]. Many of the researches focuses on the
communication protocol such as the multicast steps to
minimize the quantity of data that are needed to communicate
using procedures, for example, dead retribution.
Simulation are well known for copying the real life
systems and organizational processes with the objective of
making the improvements and the efficiency of the system [4].
The prototype application part would be used to test run the
distributed simulation with various input parameters with
objective of determining the execution speed of the cloud
infrastructure.
III. CONCLUSION AND FUTURE WORK
The distributed simulation is continued to be a very important
part of the research. The plush part of literature has been
advanced addressing complication in the part of simulations
such as the synchronization to make sure that the correct result
are produced. Future research of this theme should satisfy the
address requirements and the limitations found from the
application just as the significant changes made in the
processing stage and programming.
REFERENCES
[1] Fujimoto, R. M. 2001. “Parallel and Distributed
Simulation Systems”. In Proceedings of the 2001
Winter Simulation Conference, edited by B. A. Peters
et al., 147–57. Piscataway, New Jersey: IEEE.
[2] Taylor, S J. E. 2018. “Distributed Simulation: State-of-the-
Art and Potential for Operational Research”.
European Journal of Operational Research, doi:
10.1016/j.ejor.2018.04.032.
[3] Visti, H., T. Kiss, G. Terstyanszky, G. Gesmier, and S.
Winter. 2016. “MiCADO: Towards a Microservice-
Based Cloud Application-Level Dynamic
Orchestrator”. In Proceedings of the CEUR
Workshop, Vol. 1871.
[4] Yin, R. K. 2003. Case Study Research : Design and
Methods. Thousand Oaks, CA: Sage.