Abstract:
Modeling and simulation (M&S) techniques play a vital role in various domains such as engineering, healthcare, finance, and transportation. They enable decision-making processes, facilitate system analysis, and aid in predicting system behavior. With the growing complexity of systems and the need for efficient and cost-effective solutions, there is a demand for accessible and scalable modeling and simulation platforms.
This paper presents the design and implementation of a Modeling and Simulation as a Service (MSaaS) framework, which aims to provide M&S capabilities as a cloud-based service. The proposed framework leverages the benefits of cloud computing, such as scalability, on-demand resource allocation, and cost efficiency, to make M&S more accessible to a wider range of users.
The design of the MSaaS framework encompasses several key components, including a user interface, simulation engine, modeling tools, and a cloud infrastructure. The user interface provides a web-based portal that allows users to interact with the system, define simulation scenarios, and analyze results. The simulation engine executes the models and generates simulation results, while the modeling tools enable users to build and customize models based on their specific requirements. The cloud infrastructure ensures the availability of computational resources to support concurrent simulations and handle varying workloads.
The implementation of the MSaaS framework involves the utilization of modern web technologies, cloud computing platforms, and simulation libraries. The framework adopts a modular and extensible architecture, facilitating the integration of different simulation techniques and supporting various modeling paradigms.
The benefits of the proposed MSaaS framework include improved accessibility, reduced infrastructure costs, increased collaboration opportunities, and enhanced scalability. Users can access the M&S capabilities without the need for extensive hardware and software setup, enabling organizations to focus on their core competencies and reduce time-to-market for new products and services.
The paper concludes with a discussion of potential future developments and challenges in the field of Modeling and Simulation as a Service, such as security concerns, integration with other cloud-based services, and the incorporation of emerging technologies like artificial intelligence and machine learning.
Keywords: modeling and simulation, cloud computing, Modeling and Simulation as a Service, MSaaS, simulation engine, modeling tools, cloud infrastructure.
DESIGN AND IMPLEMENTATION OF MODELING AND SIMULATION AS A SERVICE, GET MORE COMPUTER SCIENCE PROJECT TOPICS AND MATERIALS
