Reference number : GC-2017-Q1-03113, amendment number : , agreement type : G, recipient legal name : Doucette, John (University of Alberta), recipient country : CA, recipient province : nan, recipient city : Alberta, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Despite considerable efforts taken to provide physical protection of cables, North American networks still experience frequent cable cuts and outages. For more traditional networks of the type used for basic voice or data, outages can result in severe financial losses. Given the critical nature of many of the applications that emerging networks are intended to carry (medical-grade applications, first responder applications, etc.), the consequences of failure could be much more extreme. And yet the very sparse nature of many networks&rsquo; underlying infrastructure makes them inherently un-survivable. Resilience against widespread catastrophic correlated failures is virtually out of reach for modern public network infrastructures. 
 
Modern networks employ survivability mechanisms to provide restoration in the face of cable cuts or other failures. This requires having spare capacity on standby, permitting failed traffic to be rerouted. Doing so in an optimal fashion can be a difficult problem. Current solutions utilizing linear programming approaches are widespread in the literature, where most models aim to ensure a network will survive a single failure. However, multiple failures can overlap in time; it has been shown analytically that multi-failure scenarios are the main cause of network unavailability. In order to provide higher network reliability and connection availability, survivability schemes must adapt to handle multiple failures. While work has been done to provide enhanced survivability of critical applications, there are many opportunities to develop more advanced techniques to further enhance survivability and availability. The growing prevalence of critical applications on modern networks will significantly alter the way they will evolve when compared to best effort approaches of today. Determining how to design networks to meet specified levels of availability is still very much an open question. 
 
The program outlined by this proposal includes three key objectives. 
(1) Improved Network Availability Models: In order to incorporate availability within the network design approach, better network availability models are needed, primarily those that account for survivability mechanisms deployed in most modern networks. 
(2) Optimization Models for High Availability Network Design: Next we will focus on linear programming models for design of survivable networks to guarantee specific connection availability. Multi-period planning and topology optimization will be incorporated into these approaches. 
(3) Heuristic Approaches for Large Scale High Availability Network Optimization Problems: Although optimal design models of the type described above are difficult to solve, heuristics applied to basic network design approaches have shown promise in obtaining near optimal designs. We will also seek to apply these approaches to disaster-resilient network design., program purpose french : Despite considerable efforts taken to provide physical protection of cables, North American networks still experience frequent cable cuts and outages. For more traditional networks of the type used for basic voice or data, outages can result in severe financial losses. Given the critical nature of many of the applications that emerging networks are intended to carry (medical-grade applications, first responder applications, etc.), the consequences of failure could be much more extreme. And yet the very sparse nature of many networks&rsquo; underlying infrastructure makes them inherently un-survivable. Resilience against widespread catastrophic correlated failures is virtually out of reach for modern public network infrastructures. 
 
Modern networks employ survivability mechanisms to provide restoration in the face of cable cuts or other failures. This requires having spare capacity on standby, permitting failed traffic to be rerouted. Doing so in an optimal fashion can be a difficult problem. Current solutions utilizing linear programming approaches are widespread in the literature, where most models aim to ensure a network will survive a single failure. However, multiple failures can overlap in time; it has been shown analytically that multi-failure scenarios are the main cause of network unavailability. In order to provide higher network reliability and connection availability, survivability schemes must adapt to handle multiple failures. While work has been done to provide enhanced survivability of critical applications, there are many opportunities to develop more advanced techniques to further enhance survivability and availability. The growing prevalence of critical applications on modern networks will significantly alter the way they will evolve when compared to best effort approaches of today. Determining how to design networks to meet specified levels of availability is still very much an open question. 
 
The program outlined by this proposal includes three key objectives. 
(1) Improved Network Availability Models: In order to incorporate availability within the network design approach, better network availability models are needed, primarily those that account for survivability mechanisms deployed in most modern networks. 
(2) Optimization Models for High Availability Network Design: Next we will focus on linear programming models for design of survivable networks to guarantee specific connection availability. Multi-period planning and topology optimization will be incorporated into these approaches. 
(3) Heuristic Approaches for Large Scale High Availability Network Optimization Problems: Although optimal design models of the type described above are difficult to solve, heuristics applied to basic network design approaches have shown promise in obtaining near optimal designs. We will also seek to apply these approaches to disaster-resilient network design., agreement title english : Design and Optimization of High-Availabilty Neworks, agreement title french : Design and Optimization of High-Availabilty Neworks, agreement number : RGPIN, agreement value : 120000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada