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Development of a Big Data Enabled Web GIS Framework Driven by High Performance Computing

Authors: Zachery Slocum*, University of North Carolina - Charlotte, Wenwu Tang, University of North Carolina - Charlotte
Topics: Geographic Information Science and Systems, Cyberinfrastructure
Keywords: Web, GIS, Big, Data, HPC, Framework
Session Type: Paper
Presentation File: No File Uploaded

The HPC-Enabled Web GIS Framework described contributes to the Web GIS domain through its incorporation of HPC and IT solutions. The use of Docker allows this framework to be implemented into existing Docker Swarm clusters as well as easily run on one or more machines during testing. Friendliness to the system administrator goes a long way, and this framework aims to satisfy that request by configuring the applications nearly identically to non-clustered applications. Docker Swarm allows the clustering to be handled transparently in the background. The framework is easy to scale, with automatic reconfiguration when necessary. The framework’s novelty is also apparent in its use of Traefik and Docker Swarm to provide many machines to accept requests and route them accordingly. The framework’s use of GeoServer in a cluster unaware configuration is a limitation while updates are being made to the GeoServer configuration. However, I argue this is a feature, not a bug, because it allows changes to be completed before propagating to running containers. Docker Swarm allows for rolling updates to worker containers, relieving disk and network stress on the NFS host during reconfiguration while avoiding service disruptions.
Web GIS will continue to gain performance improvements from the previously pioneered high-performance computing space. As geographic information scientists, we must constantly look to the trending technologies in computer science to improve our own use cases. Big data will continue to grow and present a challenge for many years to come.

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