NEXT GENERATION MODELING : A GRAND CHALLENGE

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NEXT GENERATION MODELING : A GRAND CHALLENGE

First, I define a few key dimensions of modeling, such as economy, culture and technology, and follow up with how these dimensions will change in the future, and where our research may lead. I conclude the paper with an overview of research we are performing to help move modeling forward by addressing some aspects of these dimensions. Our research aim is to demonstrate key problems in modeling, with partial solutions, along with addressing what is possible for the future to tackle the “grand challenges” of modeling. INTRODUCTION The field of Simulation is usually combined with the term “Modeling” to form “Modeling and Simulation” or perhaps “Simulation Modeling,” Regardless of these terminological differences, modeling plays a key role not only for simulation [1], but for science, engineering and art. To model is to create a structure that captures interesting or noteworthy attributes of a target object. The model of the RMS Queen Mary ship that I have on my shelf is a small metallic piece, and it allows me to experience the ship without setting foot on it. I can become familiar with something that is literally outside of my grasp. By making a target object smaller (as for the Queen Mary) or larger (as for a hexagonal benzene molecule), familiarity with the target is made possible. Modeling dynamical systems has many similarities with these scale models; we need to explore these connections now that technology has permitted us to construct scale models with greater efficiency and economy. Modeling is an amazingly diverse topic whose coverage can be found in just about every discipline. It differs from Analysis or Execution in that the topical area does not command as much attention in the Simulation literature as for Analysis (the mathematical and statistical study of dynamical system behavior) and Execution (the algorithmic analysis of computational efficiency). Modeling does pose major challenges, whose solutions will be felt far outside of the simulation sphere. People speak of models in many ways. A computer program could be seen as a model. Someone may say “I have created a model” but when put to the question of representation, it turns out that they have created a computer program. Then, the question becomes one of representation, which is central to modeling. What representational vehicle did they use, and was program the only representation, or did the model construction begin with other languages and forms and then undergo a sequence of transformations to yield the final program? The area of modeling is all about these forms and the construction process. Modeling is concerned what materials are used to make a structure, how one chooses these materials, and how one interfaces with them. It is a mistake to construe modeling in Computer Simulation to be fundamentally different than modeling found in other areas, such as scale models of the Queen Mary, Eiffel Tower, or a working miniature gas-powered turbine. Also, tasks such as verification and validation are also critical to the overall process of simulation, but they are not the core part of modeling per se; instead, they affect modeling and serve as one of several feedback mechanisms, which help to adjust model structure. One might say that the purpose of modeling is system validation, but apart from the observation that achieving validity is only one aspect of the process of modeling, it is like saying that the purpose of driving is to get to the store. Driving and modeling have their own particular knowledge, ontologies, and processes, bu the means and ends are separate. Modeling, as an interface, lies midway between the human doing the modeling and the thing being modeled. Media become paramount in discussions of model definition, style, aesthetics, and how models are crafted. HISTORY The subject of history might better termed timeline, where we look at the past, the present, and project into the future. For considering grand challenges for modeling, it may behoove us to begin with the future and then return back to the past to collect artifacts relevant to the modeling enterprise. What will history say of our modeling efforts today and in the future? Can we imagine a futuristic modeling environment? One way to imagine the future of modeling is to read books on science fiction and watch modern movies, with their ever-increasing dependence on the latest technologies in computer graphics and post-production techniques that blur the line between “reality” and “simulation.” Disney’s 1982 movie Tron envisaged a world inside of the computer, with users having their own representative avatars working against the Master Control Program (MCP). The MCP, whose counterpart in the real world, ran a large company, played the role of antagonist, while the protagonist aimed to shut down the evil MCP. The 3D, graphically-rendered computer landscape, very advanced for its time, showed a futuristic computing device, along with its working innards. Another popular TV series, Star Trek: The Next Generation, contained a special environment called the Holodeck. The Holodeck could reproduce the effects of any virtual scene, set of objects, or level of sensory immersion and engagement. In many ways, the Holodeck becomes the modeler’s nirvana since anything can be created and experienced. To program the Holodeck is to craft the ultimate simulation, one where it is not possible to differentiate between the Holodeck experience and “real life.” It was never made clear what Holodeck programs actually looked like, or how one created models in the Holodeck, but it seems doubtful that Holodeck programmers used paper, flat screens and sharp writing utensils. It would appear that part of our challenge is to figure out how to achieve similar tasks in modeling, with the assumption that our state of technology will improve to the point where the Holodeck will eventually become achievable. In fact, the Holodeck and similar futuristic features found in recent shows, books, and movies (such as Dr. Who, Gibson’s Neuromancer, and The Matrix film) help us to construct Gedanken (i.e., mind) experiments. For example, imagine that you are inside of a Holodeck and that it is not possible to ask for paper, a computer keyboard, mouse, or writing instruments. How will you model now that you have been deprived of your dependencies? Rather than being an easily dismissed fantasy, this sort of philosophical quandary should help to cast a new foundation for grand challenge modeling. We should and must envisage modeling as it would be on the Holodeck. Efforts that help us to answer these questions are likely to lead to partial solutions to the grand challenge questions that we pose for Modeling. For an example of what we might create in the Holodeck, Figure 1 and Figure 2 suggest ways in which we might design or observe TCP/IP networks. Elam and Hanberger [2] created a 3D movie with visual imagery accentuating the flow of packets through routers. There are two ways of looking at this work: a visualization of more abstract phenomena, or as a precursor to modeling research for local area networks and the Internet. Figure 1: TCP/IP router, which directs IP packet flow, Courtesy of Gunilla Elam, Ericsson Media Lab, 1999. Figure 2: Packets being routed over the Internet, Courtesy of Gunilla Elam, Ericsson Media Lab, 1999. Some of the difference depends on an ontological status with which we endow certain objects. Perhaps, these figures represent the “real” router models, whereas the flat models are typographic or diagrammatic visualizations? If we return to the past by winding back the clock 5000 years or so, our first human attempts at modeling would have been small figurines and objects, likely of religious or ritual importance. Archeological digs of the Middle East are strewn with such finds, representing spawning grounds for human civilization. The clay tokens in Babylonia were originally used for accounting purposes [3] where they resembled the items bartered or exchanged (sheep, oil, grain). The tokens were placed inside clay envelopes, the ancient equivalent of modern sealed paper envelopes and digitally watermarked data. As the envelopes had to be frequently opened, new wedge-shaped marks were made on the outside of the clay, representing our first written language. Once cuneiform had its scribes and artisans, the tokens fell into disuse since it became inefficient to make these costly contents. The clay figurines and tokens were some of our first models. While we have progressed into more stylistic and flatter forms of model representation, this progression is likely due to cost efficiencies introduced by the new technologies. Virtual clay tokens and figurines would have worked wonders in the Holodeck, but the use of them was less efficient than cuneiform, and more expensive in labor. We must carefully consider all tradeoffs from the past, before imagining that representations evolved due to more ideal forms. Our forms advanced to accommodate existing technologies. TECHNOLOGY Given what we may strive for in terms of technological progress, we should emphasize model definition and construction in cutting edge environments, capable of supporting a truly engaging and immersive experience. Thus, modeling efforts centered on various new forms of computing are to be encouraged. We have come a long way from the movie Tron, to where we can simulate almost photo-realistic real-time objects and action on an inexpensive home computer. The problems come into play when considering the limited immersion gained by these displays. We realize that we are outside of the environment, and not really part of it, and that we cannot smell, feel, or touch objects.

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