Massive GIS Database System with Autonomic Resource Management

Abstract

GIS application hosts are becoming more and more complicated. Thus, their management is more time consuming, and reliability decreases with the complexity of GIS applications increasing. We have designed, implemented, and evaluated, a virtualized whole Large Scale Distributed Spatial Data Visualization System for optimizing maintainability and performance when handling large amount of GIS data. We employ the virtual machines (VMs) technique, load balance cluster techniques, and autonomic resource management to improve the system's performance. The proposed system was prototyped on TerraFly [1], a production web map service, and evaluated using actual TerraFly workloads. The results show that the virtual TerraFly system has both good performance and much better maintainability. Our experiments show that the proposed Virtual TerraFly Geo-database system has doubled the reliability, and saved 20-30% computing resources cost compared to current static peak-load physical machine node allocations.