Abstract:
Disasters can cause severe service disruptions due to large-scale correlated cascading failures in telecom networks. Major network disruptions due to disasters - both natural (e. g., Hurricane Sandy, 2011 Japan Tsunami) and human-made (e. g., 9/11 terrorist attack) deprive the affected population of essential network services for weeks and severely hamper rescue operations. Many techniques exist to provide fast network protection, but they are optimized for limited faults without addressing the extent of disaster failures. Thus, there is a pressing need for novel robust survivability methods to mitigate the effects of disasters on telecom networks. While researchers in climatology, geology, and environmental science have been studying how to predict disasters and assess disaster risks for certain regions, networking research can exploit this information to develop novel methods to prepare networks to handle disasters with the knowledge of risky regions and to better prepare them for a predicted disaster. The events during the aftermath of a disaster should also be considered. For instance, methods to re-arrange network resources and services on a partially damaged network, which is the property of a self-organizing network, should be developed, and new algorithms to manage the post-disaster traffic deluge and to relieve the rescue operations after a disaster, with the knowledge of the post-disaster failures, should be investigated. Since cloud services today are an integral part of our society and massive amounts of content/services have been created and shared over the cloud, loss/disruption of critical content/services caused by disasters can significantly affect the security and economic well being of our society. As the network is becoming increasingly an end-to-content (vs. end-toend) connection provider, we have to ensure reachability of content from any point of a network, which we call content connectivity (in contrast to network connectivity) after disaster failures. This article presents the nature of possible disruptions in telecom networks caused by disaster events, and sheds light on how to prepare the network and cloud services against disasters, and adapt them for disaster disruptions and cascading failures.
