Survivability in ATM networks

n ATM network design, self-healing is the ability of the network to continue to provide service in the event of failures, and this compromises both planning and operational aspects. The planning aspect involves optimal/near-optimal network design problems while the operational aspect deals with the implementation of protection schemes using restoration mechanisms, for allocating spare capacity to the network to be used in case of a failure event. This project investigates the survivability (i.e. restoration ratio) - here defined by means of the aggregate restoration ratio - in existing ATM networks based on various spare capacity distribution schemes, with the goal to (1) compare the network survivability for link and path restorations, and (2) determine the effects of various traffic and design related patterns on the restoration ratio.

Survivability in ATM networks

n ATM network design, self-healing is the ability of the network to continue to provide service in the event of failures, and this compromises both planning and operational aspects. The planning aspect involves optimal/near-optimal network design problems while the operational aspect deals with the implementation of protection schemes using restoration mechanisms, for allocating spare capacity to the network to be used in case of a failure event. This project investigates the survivability (i.e. restoration ratio) - here defined by means of the aggregate restoration ratio - in existing ATM networks based on various spare capacity distribution schemes, with the goal to (1) compare the network survivability for link and path restorations, and (2) determine the effects of various traffic and design related patterns on the restoration ratio.

A holistic optimization framework for forest machine trail network design accounting for multiple objectives and machines

Ground-based mechanized forestry requires the traversal of terrain by heavy machines. The routes that they take are often called “machine trails” and are created by removing trees from the trail and placing the logs outside it. Designing an optimal machine trail network is a complex locational problem that requires understanding how forestry machines can operate on the terrain, as well as the trade-offs between various economic and ecological aspects. Machine trail designs are currently created manually based on intuitive decisions about the importance, correlations, and effects of many potentially conflicting aspects. Badly designed machine trail networks could result in costly operations and adverse environmental impacts. Therefore, this study was conducted to develop a holistic optimization framework for machine trail network design. Key economic and ecological objectives involved in designing machine trail networks for mechanized cut-to-length operations are presented, along with strategies for simultaneously addressing multiple objectives while accounting for the physical capabilities of forestry machines, the impact of slope, and the operating costs. Ways of quantitatively formulating and combining these different aspects are demonstrated, together with examples showing how the optimal network design changes in response to various inputs.