Scalable Cloud Infrastructure Architecture for Distributed Simulation

Question: Discuss about the Scalable Cloud Infrastructure Architecture for Distributed Simulation. Answer: Problem To Be Solved The problem that is to be solved in this research paper is about a cloud infrastructure and then this paper proposes a solution to all the problems that is attributed to a single model that is simulated on particular cloud platform. Cloud computing is basically a model that enables the network access that are on demand for sharing a pool of resources [6]. The service models of cloud are mostly chosen with the type of resource which is taken. The distributed simulation involved with cloud computing helps to study the methodologies and the techniques which are needed for executing simulation models and are also used for defining the simulation models on architectures of distributed computing [2]. A distributed simulation is generally a program software that are used for evolution of models for some of the abstract or real system. To evaluate the systems even before they are built, the process if simulation is used. Simulation also affects the changes that are on the existing systems. T he simulation process mostly uses set of variables. The distributed simulation depends on dividing the simulation model over many execution units. The entire execution unit manages only a single part of model. In simulation process, execution process handles the local event list and also generates events logically that are needed for delivery for executing the remote units [7]. Simulation process allows all processor to control a part of state space and small fraction of events. To integrate the simulators, which are distributed geographically, are done by distributed simulation. Research Hypothesis The hypothesis of this research paper is that by the end of this research paper, different techniques for simulation are expected to be connected and then work together so that they can facilitate the complex and large models that can be run, analyzed in many cloud platforms, and replicated. The hypothesis made in this paper helps to improve the performance, scalability, and execution speed and also reduces the cost of modeling [5]. The contributions that were made while working on this thesis is the deployment of distributed simulation on different cloud infrastructure for the testing on user.III.Contribution Of Research In todays modern digitization era, the computing architectures and the networking systems brings the system of computer parallel to masses, which generally increases the potential number of users for those kinds of system. Cloud computing is a process that allows all the applications to scale the resources that are offered from large pool. The cloud and the multi - core processor systems requires applications that are modified to get an advantage on features that are mainly provided by them. In this technological era, the activities that are included in the business are mainly computerized and to access them from anywhere and at anytime is a way to remain competitive to achieve their business goals. By the process of cloud computing, the workflows of the businesses can be run made smooth, enabling a high performance in their business [4]. The technology of distributed simulations mainly gains the significance mainly in three different communities. The different communities are commun ity of high performance, community of defense and the gaming industry that mainly focuses on time management. The beginning of distributed simulation was in the year 2005. The standards of interoperability were being investigated that were based on format of data exchange and also the protocols for CSPs. There were also use of emulators used for feasibility study and are also used to demonstrate the benefits of the stakeholders when the emulators were adopted. Evaluating The Results Auto-scaling of the cloud infrastructure helps to allow the safe running of the distributed simulation on all the models involved in supply chain and the manufacturing industries with reliability and speed. This paper has stuffs collected from many literature reviews, which describes the PaaS, SaaS and IaaS infrastructure [1]. The methodology that is involved in this research paper is a case study approach. The data that are involved in this research are collected from the assembly line of production. The program fragment of the prototype will be developed and the distributed simulations of test run for various replications are also implied in this research paper. Results Achieved The case study that is highlighted in this research paper is about Henry Ford of Ford Automobile Company who aims to produce high speed cars at lower production cost [3]. The research paper also shows the future aim of the Ford Automobile Company and the steps that are involved with the company for distributed simulation. References D'Angelo, G., 2011. Parallel and distributed simulation from many cores to the public cloud,Proceedings of the 2011 International Conference on High Performance Computing and Simulation, HPCS 20112011, pp. 14-23. Taylor, S.J.E., Bhli, L., Wang, X., Tuner, S.J. and Ladbrook, J., 2005. Investigating distributed simulation at the Ford motor company,Proceedings - IEEE International Symposium on Distributed Simulation and Real-Time Applications, DS-RT2005, pp. 139-147. Ford Motor Company. 2017. 100 Years of the Moving Assembly Line. [ONLINE] Available at: https://corporate.ford.com/innovation/100-years-moving-assembly-line.html. [Accessed 22 November 2017]. Anagnostou, A. and Taylor, S.J.E., 2017. A distributed simulation methodological framework for OR/MS applications.Simulation Modelling Practice and Theory,70, pp. 101-119. Gabriele DAngelo. Parallel and Distributed Simulation from Many Cores to the Public Cloud. Proceedings of the 2011 International Conference on High-Performance Computing and Simulation (HPCS 2011), Istanbul (Turkey), IEEE, July 2011. ISBN 978-1-61284-382-7. Soliman, H.M. and Elmaghraby, A.S., 1996. Efficient clustered adaptive-risk technique for distributed simulation,IEEE International Symposium on High Performance Distributed Computing, Proceedings1996, pp. 383-388. Fujimoto, R.M., 2001. Parallel and distributed simulation systems,Winter Simulation Conference Proceedings2001, pp. 147-157