Automatically Switched Optical Network (ASON) is exciting technology in next generation optical
network. And the reliable control plane plays a crucial role in creating high-level services in the transport network based
on the Generalized Multi-Protocol Label Switching (GMPLS) or Automatically Switched Optical Network. The new
survivability testbed is introduced in this paper. Different network performance parameters, especially about protection
and restoration parameters, could be collected or analyzed in this testbed.
T-MPLS is regarded as one of the most important transport technologies in the next generation network, it a
connection oriented packet transport technology develop from MPLS techniques, now defined by ITU-T SG13 &
SG15. In this paper, we analyze the architecture of the transport MPLS networks, the most important building
blocks for the modular design of the common T-MPLS equipment are introduced. And based on the functional
blocks, a four-layer simulation T-MPLS node structure is developed. And the simulation environment is introduced.
Many kinds of research can be done using this T-MPLS simulation tool, such as the research of the feasibility
T-MPLS design, the inter-working between the T-MPLS and the PWE.
Network survivability has been one of the key topics when researching the optical network. For network
survivability, select two routes should be selected that are disjoint when computing the working route and protecting
route or restoring route. The purpose of the shared-protection algorithms under Shared Risk Link Group (SRLG)
constraint is to search two routes that are disjoint from SRLG. Two shared-protection algorithms under Shared Risk Link
Group (SRLG) constraint will be presented; they are KWFF and IFF algorithms. In the KWFF algorithm, the K-Shortest-
Path (KSP) strategy is introduced on every wavelength plane to search usable resources adequately in the network, the
working route and protecting route on every wavelength plane can be selected from the backup route set. And with the
iterative strategy and the double weights of link, IFF algorithm could avoid the trap that can result in deteriorating the
network performance. The simulation and results analysis will be in terms of two parts, the one is from the network
performance, and other one is from the resources utilization. From the simulation results, it will be found that compared
with other algorithms, KWFF and IFF algorithms could decrease the block probability and improve the performance in
This paper focuses on the survival mechanisms against single link failure for optical QoS services in ASON (Automatically Switched Optical Network). The new protection and restoration methods and optical QoS services enabled by ASON also bring new requirements. Correspondingly, the component functions in ASON control plane, such as Connections Controller, Link Resource manager and Routing Controller are extended. According to the survival level of the QoS service requested, we divide the traffic into five types, viz. 1+1, 1:1, shared-mesh, rerouting and extra traffic. Optical QoS services and resource preemption are realized in our simulation platform. Extensive simulations are performed concerning failure localization time, failure recovery time, recovery success ratio and network resource utilization.
<i>p</i>-cycle provides a new protection scheme which provides fast protection switching time as that in ring networks and high resource efficiency as that in mesh networks. Extensive research has shown that the concept of <i>p</i>-cycle can also be applied to Automatically Switched Optical Network (ASON), which is the direction of the next generation optical network. This paper proposes a novel dynamic <i>p</i>-cycle algorithm in ASON named Routing in Spare plus Protecting Capacity Dynamic <i>p</i>-cycle Algorithm (RSPC-DP). Different from traditional dynamic <i>p</i>-cycle algorithms, the proposed algorithm takes traffic forecast matrix into account, and it is capable of tracing the changes of network environment and dynamic traffic matrix on-line. Extensive simulation results show that the proposed algorithm outperforms the existing algorithms significantly.