Research On Large Scale Distributed DynamicVirtual Environment Simulation Based On Computing Grid

Large-scale virtual environment simulation and terrain visualization have been regarded as a key technique in the field such as watershed hydrological analysis, climate analysis and simulation, flood routing simulation, disaster prevention and alleviation, urban planning, virtual traveling, online games, and so on. The advances in Remote Sensing (RS) make it possible to acquire geographical and spatial data with higher resolution.Unfortunately, large-scale terrain visualization is not widely used and the performance is not satisfied due to the processing power limitations. In the future, remote online cooperative visualization and simulation will become true with the advances in computer networks and its wide usage.Grid computing, regarded as the Next Generation Internet, can help aggregate the resources on the Web, such as supercomputers, large-scale storage infrastructures, PCs, sensors, software, and computer peripherals, to a"Virtual Supercomputer"to break the processing power limitations in large-scale terrain visualization and remote cooperative simulations.In this thesis, a hierarchical architecture of grid computing based large scale distributed dynamic terrain visualization and simulation is proposed.The architecture is composed of grid sites, communication and authentication protocols, individual resource management, global resource management, simulation applications, and grid portal, in a view from bottom to top.Based on the architecture proposed above, some key algorithms and system models were proposed, such as:(1) Security Aware and Fault-Tolerant Scheduling (SAFTS) algorithm based on adaptive job replications. In risky and failure-prone grids, SAFTS is robust due to its adaptive job replications and rescheduling mechanism. Simulation results generated from SimGrid package show that the performance of SAFTS is better than non-security-aware scheduling algorithms based on fixed-number job replications and SAFTS is fault tolerant and scalable.(2) View-dependent based modified Level of Details (LOD) algorithm (VMLOD) for large-scale terrain visualization. In VMLOD, continuous LOD model is constructed according to the view position. Simulation results show that VMLOD is faster than conventional LOD algorithms and it can draw the terrain without slits.(3) A hierarchical architecture of massive data management. The architecture is composed of data storage nodes, data transferring and processing system, and computational facilities. The architecture supports global massive data management, topology management, meta-data management, and data concurrency. Experiment results show that the data management architecture here developed is highly efficient, reliable and robust. After comprehensive theory study of above mentioned key problems, a prototype system for Grid-based Large-scale Terrain Visualization Simulation(GLTVS) is constructed based on the above research results, which mainly consists of hardware and support software, including networking communication sub-system, computing sub-system, database sub-system, visualization terminals, control console terminal, and grid Operating System.In GLTVS, processing power is provided by the grid sites and the data are transferred transparently through grid sites and tasks. The grid storage subsystem provides high data availability and reliability, including file and data transferring, data replication and recovery. Computing sub-system includes various homogenous and heterogeneous computing resources with different computing powers.The common functional modules aggregate the applications such as environment visualization, simulation strategies and some other specific subsystems.In GLTVS, all the grid services are provided through a grid portal which makes the service easily accessible, safe, high usability, and can be easily manipulated by nonprofessional users. Tests of GLTVS were carried out on LAN (Local Area Network) gird computing platform. Results show that the hardware and software architecture of GLTVS we developed is efficient, reliable and robust. The response time of database server is within 1.5 seconds and can satisfy real time operation.