This paper proposes a recommendation-based bandwidth calendaring system for packet transport networks. The system provides a user-portal interface with which users can directly reserve packet transport resources. In this regard, the system recommends multi-grade (e.g., multi-price) reservation plans. By adjusting grades of plans in accordance with network resource utilization, this system provides not only reservation flexibility for users but also efficient utilization of network resources. For recommending multi-grade plans, pre-computation of resource allocation is required for every time slot. Because the number of time slots is huge, we also propose an algorithm for fast computation of resource allocation based on time-slot aggregation. Our evaluation suggests that our algorithm can produce a sub-optimal solution within quasi-real time for a large-scale network. We also show that our recommendation-based system can increase the service-provider-revenue in peaky traffic demand environments.

This paper proposes fast repairing methods that uses hierarchical software defined network controllers for recovering from massive failure in a large-scale IP over a wavelength-division multiplexing network. The network consists of multiple domains, and slave controllers are deployed in each domain. While each slave controller configures transport paths in its domain, the master controller manages end-to-end paths, which are established across multiple domains. For fast repair of intra-domain paths by the slave controllers, we define the optimization problem of path configuration order and propose a heuristic method, which minimizes the repair time to move from a disrupted state to a suboptimal state. For fast repair of end-to-end path through multiple domains, we also propose a network abstraction method, which efficiently manages the entire network. Evaluation results suggest that fast repair within a few minutes can be achieved by applying the proposed methods to the repairing scenario, where multiple links and nodes fail, in a 10,000-node network.