Analysis domain model for shared virtual environments

The field of shared virtual environments, which also encompasses online games and social 3D environments, has a system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model

Network architecture for large-scale distributed virtual environments

Distributed Virtual Environments (DVEs) provide 3D graphical computer generated environments with stereo sound, supporting real-time collaboration between potentially large numbers of users distributed around the world. Early DVEs has been used over local area networks (LANs). Recently with the Internet's development into the most common embedding for DVEs these distributed applications have been moved towards an exploiting IP networks. This has brought the scalability challenges into the DVEs evolution. The network bandwidth resource is the more limited resource of the DVE system and to improve the DVE's scalability it is necessary to manage carefully this resource. To achieve the saving in the network bandwidth the different types of the network traffic that is produced by the DVEs have to be considered. DVE applications demand· exchange of the data that forms different types of traffic such as a computer data type, video and audio, and a 3D data type to keep the consistency of the application's state. The problem is that the meeting of the QoS requirements of both control and continuous media traffic already have been covered by the existing research. But QoS for transfer of the 3D information has not really been considered. The 3D DVE geometry traffic is very bursty in nature and places a high demands on the network for short intervals of time due to the quite large size of the 3D models and the DVE application requirements to transmit a 3D data as quick as possible. The main motivation in carrying out the work presented in this thesis is to find a solution to improve the scalability of the DVE applications by a consideration the QoS requirements of the 3D DVE geometrical data type. In this work we are investigating the possibility to decrease the network bandwidth utilization by the 3D DVE traffic using the level of detail (LOD) concept and the active networking approach. The background work of the thesis surveys the DVE applications and the scalability requirements of the DVE systems. It also discusses the active networks and multiresolution representation and progressive transmission of the 3D data. The new active networking approach to the transmission of the 3D geometry data within the DVE systems is proposed in this thesis. This approach enhances the currently applied peer-to-peer DVE architecture by adding to the peer-to-peer multicast neny_ork layer filtering of the 3D flows an application level filtering on the active intermediate nodes. The active router keeps the application level information about the placements of users. This information is used by active routers to prune more detailed 3D data flows (higher LODs) in the multicast tree arches that are linked to the distance DVE participants. The exploration of possible benefits of exploiting the proposed active approach through the comparison with the non-active approach is carried out using the simulation­based performance modelling approach. Complex interactions between participants in DVE application and a large number of analyzed variables indicate that flexible simulation is more appropriate than mathematical modelling. To build a test bed will not be feasible. Results from the evaluation demonstrate that the proposed active approach shows potential benefits to the improvement of the DVE's scalability but the degree of improvement depends on the users' movement pattern. Therefore, other active networking methods to support the 3D DVE geometry transmission may also be required

MOLNs: A cloud platform for interactive, reproducible and scalable spatial stochastic computational experiments in systems biology using PyURDME

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools, a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments

Advances in Grid Computing

This book approaches the grid computing with a perspective on the latest achievements in the field, providing an insight into the current research trends and advances, and presenting a large range of innovative research papers. The topics covered in this book include resource and data management, grid architectures and development, and grid-enabled applications. New ideas employing heuristic methods from swarm intelligence or genetic algorithm and quantum encryption are considered in order to explain two main aspects of grid computing: resource management and data management. The book addresses also some aspects of grid computing that regard architecture and development, and includes a diverse range of applications for grid computing, including possible human grid computing system, simulation of the fusion reaction, ubiquitous healthcare service provisioning and complex water systems

Recognition of Crowd Behavior from Mobile Sensors with Pattern Analysis and Graph Clustering Methods

Mobile on-body sensing has distinct advantages for the analysis and understanding of crowd dynamics: sensing is not geographically restricted to a specific instrumented area, mobile phones offer on-body sensing and they are already deployed on a large scale, and the rich sets of sensors they contain allows one to characterize the behavior of users through pattern recognition techniques. In this paper we present a methodological framework for the machine recognition of crowd behavior from on-body sensors, such as those in mobile phones. The recognition of crowd behaviors opens the way to the acquisition of large-scale datasets for the analysis and understanding of crowd dynamics. It has also practical safety applications by providing improved crowd situational awareness in cases of emergency. The framework comprises: behavioral recognition with the user's mobile device, pairwise analyses of the activity relatedness of two users, and graph clustering in order to uncover globally, which users participate in a given crowd behavior. We illustrate this framework for the identification of groups of persons walking, using empirically collected data. We discuss the challenges and research avenues for theoretical and applied mathematics arising from the mobile sensing of crowd behaviors

A Microscopic Simulation Laboratory for Evaluation of Off-street Parking Systems

The parking industry produces an enormous amount of data every day that, properly analyzed, will change the way the industry operates. The collected data form patterns that, in most cases, would allow parking operators and property owners to better understand how to maximize revenue and decrease operating expenses and support the decisions such as how to set specific parking policies (e.g. electrical charging only parking space) to achieve the sustainable and eco-friendly parking. However, there lacks an intelligent tool to assess the layout design and operational performance of parking lots to reduce the externalities and increase the revenue. To address this issue, this research presents a comprehensive agent-based framework for microscopic off-street parking system simulation. A rule-based parking simulation logic programming model is formulated. The proposed simulation model can effectively capture the behaviors of drivers and pedestrians as well as spatial and temporal interactions of traffic dynamics in the parking system. A methodology for data collection, processing, and extraction of user behaviors in the parking system is also developed. A Long-Short Term Memory (LSTM) neural network is used to predict the arrival and departure of the vehicles. The proposed simulator is implemented in Java and a Software as a Service (SaaS) graphic user interface is designed to analyze and visualize the simulation results. This study finds the active capacity of the parking system, which is defined as the largest number of actively moving vehicles in the parking system under the facility layout. In the system application of the real world testbed, the numerical tests show (a) the smart check-in device has marginal benefits in vehicle waiting time; (b) the flexible pricing policy may increase the average daily revenue if the elasticity of the price is not involved; (c) the number of electrical charging only spots has a negative impact on the performance of the parking facility; and (d) the rear-in only policy may increase the duration of parking maneuvers and reduce the efficiency during the arrival rush hour. Application of the developed simulation system using a real-world case demonstrates its capability of providing informative quantitative measures to support decisions in designing, maintaining, and operating smart parking facilities

Investigation and development of a tangible technology framework for highly complex and abstract concepts

The ubiquitous integration of computer-supported learning tools within the educational domain has led educators to continuously seek effective technological platforms for teaching and learning. Overcoming the inherent limitations of traditional educational approaches, interactive and tangible computing platforms have consequently garnered increased interest in the pursuit of embedding active learning pedagogies within curricula. However, whilst Tangible User Interface (TUI) systems have been successfully developed to edutain children in various research contexts, TUI architectures have seen limited deployment towards more advanced educational pursuits. Thus, in contrast to current domain research, this study investigates the effectiveness and suitability of adopting TUI systems for enhancing the learning experience of abstract and complex computational science and technology-based concepts within higher educational institutions (HEI)s. Based on the proposal of a contextually apt TUI architecture, the research describes the design and development of eight distinct TUI frameworks embodying innovate interactive paradigms through tabletop peripherals, graphical design factors, and active tangible manipulatives. These computationally coupled design elements are evaluated through summative and formative experimental methodologies for their ability to aid in the effective teaching and learning of diverse threshold concepts experienced in computational science. In addition, through the design and adoption of a technology acceptance model for educational technology (TAM4Edu), the suitability of TUI frameworks in HEI education is empirically evaluated across a myriad of determinants for modelling students’ behavioural intention. In light of the statistically significant results obtained in both academic knowledge gain (μ = 25.8%) and student satisfaction (μ = 12.7%), the study outlines the affordances provided through TUI design for various constituents of active learning theories and modalities. Thus, based on an empirical and pedagogical analyses, a set of design guidelines is defined within this research to direct the effective development of TUI design elements for teaching and learning abstract threshold concepts in HEI adaptations

Component-Based Tools for Educational Simulations

e-Learning is an effective medium for delivering knowledge and skills. In spite of improvements in electronic delivery technologies, e-Learning is still a long way away from offering anything close to efficient and effective learning environments. To improve e-Learning experiences, much literature supports simulation based e-Learning. This thesis begins identifying various types of simulation models and their features that induce experiential learning. We focus on designing and constructing an easy-to-use Discrete Event Simulation (DES) tool for building engaging and informative interactive DES models that allow learners to control the models’ parameters and visualizations through runtime interactions. DES has long been used to support analysis and design of complex systems but its potential to enhance learning has not yet been fully utilized. We first present an application framework and its resulting classes for better structuring DES models. However, importing relevant classes, establishing relationships between their objects and representing lifecycles of various types of active objects in a language that does not support concurrency demand a significant cognitive workload. To improve this situation, we utilize two design patterns to ease model structuring and logic representation (both in time and space) through a drag and drop component approach. The patterns are the Delegation Event Model, used for linking between components and delegating tasks of executing and updating active objects’ lifecycles, and the MVC (Model-View-Controller) pattern, used for connecting the components to their graphical instrumentations and GUIs. Components implementing both design patterns support the process-oriented approach, can easily be tailored to store model states and visualizations, and can be extended to design higher level models through hierarchical simulation development. Evaluating this approach with both teachers and learners using ActionScript as an implementation language in the Flash environment shows that the resulting components not only help model designers with few programming skills to construct DES models, but they also allow learners to conduct various experiments through interactive GUIs and observe the impact of changes to model behaviour through a range of engaging visualizations. Such interactions can motivate learners and make their learning an enjoyable experience

Adaptive remote visualization system with optimized network performance for large scale scientific data

This dissertation discusses algorithmic and implementation aspects of an automatically configurable remote visualization system, which optimally decomposes and adaptively maps the visualization pipeline to a wide-area network. The first node typically serves as a data server that generates or stores raw data sets and a remote client resides on the last node equipped with a display device ranging from a personal desktop to a powerwall. Intermediate nodes can be located anywhere on the network and often include workstations, clusters, or custom rendering engines. We employ a regression model-based network daemon to estimate the effective bandwidth and minimal delay of a transport path using active traffic measurement. Data processing time is predicted for various visualization algorithms using block partition and statistical technique. Based on the link measurements, node characteristics, and module properties, we strategically organize visualization pipeline modules such as filtering, geometry generation, rendering, and display into groups, and dynamically assign them to appropriate network nodes to achieve minimal total delay for post-processing or maximal frame rate for streaming applications. We propose polynomial-time algorithms using the dynamic programming method to compute the optimal solutions for the problems of pipeline decomposition and network mapping under different constraints. A parallel based remote visualization system, which comprises a logical group of autonomous nodes that cooperate to enable sharing, selection, and aggregation of various types of resources distributed over a network, is implemented and deployed at geographically distributed nodes for experimental testing. Our system is capable of handling a complete spectrum of remote visualization tasks expertly including post processing, computational steering and wireless sensor network monitoring. Visualization functionalities such as isosurface, ray casting, streamline, linear integral convolution (LIC) are supported in our system. The proposed decomposition and mapping scheme is generic and can be applied to other network-oriented computation applications whose computing components form a linear arrangement