Due to a continuous stream of technological advances, enormous amounts of traffic are aggregated onto a single fiber. The main drive for this is the cost savings that are realized due to the economy of scale. However, a major drawback is the impact of a single failure (e.g., cable cut), which can become very and even unacceptably large. This paper aims at discussing the different techniques that can be applied to deal with such circumstances.
Next generation automatic switched optical networks (ASON) show great promise in coping with increasing bandwidth demands, as they provide both on-demand bandwidth and improved switching flexibility. In a multi-layer data-centric network, such an ASON acts as a server layer and provides the topology for a client IP network. Multi-layer Traffic Engineering (MTE) enhances single-layer traffic engineering (i.e. adaptive routing) with the possibility to reconfigure the logical IP topology, utilizing the aforementioned optical flexibility in setting up and tearing down end-to-end lightpaths. To provide a robust network service, the multi-layer networks must be recoverable from different types of failures. Resilience mechanisms such as various forms of protection and restoration allow to recover from optical layer failures. In a multi-layer network however, some traffic will be forwarded through the IP layer routers, requiring a survivability scheme in this IP layer. This paper shows how MTE strategies that normally cope with changing traffic demands, can be used to provide this IP layer resilience. This is done through diverting affected IP traffic and replacing failing optical lightpaths, effectively leading to a dynamic restoration scheme. We will evaluate and compare failure performance of different types of resilience mechanisms, based on an existing MTE strategy.
As more and more traffic is transported over communication networks, network survivability becomes a key issue in network design and planning. In this paper first the need for deploying network recovery techniques at multiple layers is motivated. Then the efficient coordination of these network recovery techniques is studied. Not only static but also dynamic multi-layer survivability strategies are presented and studied in this paper: dynamic multi-layer survivability strategies benefit from the ability of the underlying transport network to provide switched connection services in order to allow reconfiguring the logical network at the time of a failure. As not only the traffic volume keeps growing, but also more and more services with distinct reliability requirements are deployed, the benefit of differentiating the multi-layer survivability strategy per traffic class is investigated in this paper. Whereas the case studies in this paper focus on the cost-efficiency of the presented strategies and techniques, also a broader theoretic discussion is given on these techniques.
Although the Optical Transport Network, based on technologies such as Wavelength Division Multiplexing and Optical Cross-Connects, offers tremendous transportation capacity, its management requires frequent manual intervention. However, as the traffic pattern offered to today's transport networks is subject to continuous changes due to the Internet traffic dominance, an optical transport network with a smart, automatic and real-time control system, denoted as Intelligent Optical Network (ION) or Automatic Switched Optical Network (ASON), is desired by network operators. Duly and correctly retrieving the changing traffic load information is a very important factor for the successful deployment of an ION. In this paper, we discuss the influence of the observation window size used for collecting the traffic load information, on the performance of an ION. By comparing the performance of an ION using different traffic observation window sizes, we show that a smaller observation window harms the network stability; while a too large observation window worsens the network reliability. We demonstrate that a suitable traffic observation window size improves the offered Quality of Service (QoS) by reconfiguring the logical layer network at the right time and in the right way.