Avoiding high impacts of geospatial events in mission critical and emergency networks using linear and swarm optimization

Geospatial events continue to plague both wireless and wireline communication networks. The immediate effect of a large scale geospatial event is generally complete or partial loss of situational awareness caused by a lack of communications and media availability in the affected area, effectively isolating many people affected. Significant challenges have been reported by emergency responders, victims, and other involved persons immediately following the recent U.S. tornados and the earthquakes worldwide. Riots and protests can also act as geospatial events that stress communications resources in a geographic area. This research develops novel optimization models to identify and mitigate geospatial vulnerabilities in network designs before they occur. We use an integer linear program (ILP) to add nodes that reduces geographic vulnerability thus preventing users from being isolated by geospatial events. To expand the scope to include more solutions and a wider range of objective functions, a swarm optimization approach was also developed. Wireless propagation models that include obstructions like buildings and other terrain features are tested with these models as well.