Study of network-service disruptions using heterogeneous data and statistical learning

• Main Author: Erjongmanee, Supaporn
• Published: Georgia Institute of Technology 2012
• Subjects: Statistical learning; Heterogeneous data; Network availability; Large-scale disturbances; Network dependence; Network disruptions; Network performance (Telecommunication); Telecommunication
• Online Access: http://hdl.handle.net/1853/43601

The study of network-service disruptions caused by large-scale disturbances has mainly focused on assessing network damage; however, network-disruption responses, i.e., how the disruptions occur depending on social organizations, weather, and power resources, have been studied little. The goal of this research is to study the responses of network-service disruptions caused by large-scale disturbances with respect to (1) temporal and logical network, and (2) external factors such as weather and power resources, using real and publicly available heterogeneous data that are composed of network measurements, user inputs, organizations, geographic locations, weather, and power outage reports. Network-service disruptions at the subnet level caused by Hurricanes Katrina in 2005 and Ike in 2008 are used as the case studies. The analysis of network-disruption responses with respect to temporal and logical network shows that subnets became unreachable dependently within organization, cross organization, and cross autonomous system. Thus, temporal dependence also illustrates the characteristics of logical dependence. In addition, subnet unreachability is analyzed with respect to the external factors. It is found that subnet unreachability and the storm are weakly correlated. The weak correlation motivates us to search for root causes and discover that the majority of subnet unreachability reportedly occurred because of power outages or lack of power generators. Using the power outage data, it is found that subnet unreachability and power outages are strongly correlated.