Optical backbone networks are becoming increasingly intelligent and flexible. These networks are able to establish high-bandwidth wavelength connections on-demand to support future network-centric applications. Choosing an efficient path in a timely manner, while considering important criteria such as operation costs and network performance, is a key problem confronting the network operators. Subtle path preferences of different dynamic routing algorithms (which are usually ignored by traditional analysis techniques) can make a significant difference in performance on mesh networks. It opens new research to advance routing algorithms in both analysis and implementation paradigms. In this paper, we propose an opportunity cost model that provides fast and accurate analysis for threshold-based online congestion-aware routing algorithms. The model is simple to compute, robust to different network topologies, and scalable. We show that our model further aids in the design of a number of new routing algorithms that can be easily applied to practical networks. In contrast to previous work, the optimal threshold values for our algorithms can be identified analytically, and the values sustain good performance on different network topologies and sizes.

Traditional backbone optical networks can take months to provision a wavelength connection. Future optical networking aims at reducing the provisioning time to a few minutes. In conjunction, new services that allow the customers to dynamically set up and take down their connections is emerging. In this paper, we introduce the problem of optimizing network resources on a reconfigurable optical backbone network that provides such dynamic optical services. The problem grows exponentially in network scale and customer's demands, thus solving the entire problem for a realistic network is impractical. We address this problem by developing a heuristic optimization procedure, combined with problem-size reduction techniques. We show that good results can be achieved using small amounts of computing power and that our solutions are within 11% of a lower bound.

As physical layer impairments play a large role in determining the ultimate performance of all-optical networks, it has attracted much attention. However, traditional survivability schemes have been designed and utilized without considering the quality of transmission at the physical layer. Recently, a few studies on QoT-aware (quality of transmission) protection were initiated to meet the reliability needs of future communications infrastructures. In this paper, we present a study of how transmission impairments caused by non-ideal characteristics of network components (such as amplifier spontaneous emission noise and crosstalk) affect the survivability under various QoT-aware protection schemes. We present heuristic QoT-guaranteed protection RWA for dynamic provisioning that forgoes multiple bit-error-rate calculations, and quantify the performance of various QoT-aware schemes. We also evaluate the tradeoff between using crosstalk-free Banyan switches and utilizing switch plane selection with non-crosstalk-free designs. It is expensive to provide QoT-guaranteed protection, but the usefulness of QoT-aware (nonguaranteed) schemes, while cost-effective, depends on the topology. Our results also show that QoT-unaware algorithms, while performing significantly worse in terms of blocking, can have slightly better post-failure performance.

Network dimensioning for wavelength-routed WDM networks has been extensively studied to maximize connection acceptance rate while minimizing the total cost. However, Internet services are increasingly generating more demands that have high-bandwidth requirements with relatively short holding times. As globalization of companies or organizations becomes a new trend, the variety of Internet service demands, in space and time, creates a more variable and unpredictable traffic model for long term network provisioning. At the same time, upgrading backbone networks remains expensive and infrequent. It is important to be able to efficiently utilize precious network resources so that low call blocking is achieved while requiring fewer upgrades when the traffic model changes. There are two kinds of dimensioning problems. First, basic dimensioning allocates network resources for a newly built network. Second, incremental dimensioning allocates extra resources for an already built network without affecting currently available resources. Historically, routing and dimensioning problems are studied together as an optimization problem. However, as integrating multiple network layers into one control platform becomes a common trend, and as higher-layer traffic that currently utilize dynamic routing imposed on logical layers increases, it is essential to plan the underlying network based on dynamic routing schemes, such as open shortest path routing (SPF). In this paper, we study basic and incremental dimensioning for dynamic routed traffic. We propose a simulation based basic dimensioning approach and introduce two new incremental dimensioning techniques: MEAN and SD. We also introduce an evolutionary traffic model and traffic load computation criteria. Simulation results show that basic dimensioning effectively reduces the topological bottlenecks, rendering 7% less blocking compared to uniform allocation. With the evolutionary traffic model, SD incremental dimensioning shows advantages over the MEAN method on most practical networks. We also compare our results with fixed routing and dimensioning approaches, showing that dynamic approaches provide better network balance and utilization.

Traffic engineering has been extensively studied to maximize network resource utilization while minimizing call blocking [1]. As the the demand for high data rate services over wide area networks (WAN) continue to grow [2], and as traffic patterns become subject to more frequent changes, resource utilization and the ability to guarantee quality-of-service become more important. However, accurate, predictive traffic models are difficult to construct [3], implying that the routing mechanism will need to adapt to the difference between the anticipated and the observed loads. Online routing based on network residual capacity plays an important role in such settings, since optimal offline solutions require knowledge of future traffic, rendering long-term optimization nearly impossible. shortest path first (SPF) based routing is fast and is currently the most widely-used online algorithm for optical networks. Many variants of SPF, like CSPF (Constrained SPF), have been proposed to further reduce blocking and network congestion. This paper focuses on the problem of online open routing for connection-oriented optical networks. As part of the major contributions of this paper, we propose a novel online, link-state based routing algorithm called reduced flow routing (RFR), an oracular optimization model, and an efficient network provisioning algorithm. The RFR algorithm uses a fast analysis of each potential route’s impact on future requests to select amongst the available choices. The strategy of RFR leverages information about network topology and residual capacity to reduce blocking by rejecting 20% less connection requests relative to other online routing algorithms with little additional cost. The RFR algorithm can be integrated readily into current and future Generalized Multi-Protocol Label Switching (GMPLS) networks as well as many other relevant networks.

Survivability becomes increasingly critical in managing high-speed networks as data traffic continues to grow in both size and importance. In addition, the impact of failures is exacerbated by the higher data rates available in optical networks. It is therefore imperative to address network survivability in an efficient manner in order to design and operate reliable networks. Transparent optical networks (TONs) provide several advantages over optically opaque networks for supporting the growing communication demands, but suffer from several drawbacks that reduce the efficacy of most applicable capacity-efficient survivability techniques. In this paper, we present a protection algorithm (for single link and/or node failures) called Streams. Streams protection is identical to 1:1 dedicated path protection in terms of recovery speed, but requires significantly less capacity. We study both online non-dynamic routing as well as (online) dynamic provisioning scenarios to compare Streams with dedicated and shared path protection in terms of capacity, blocking probability, path lengths, and recovery time/data loss, and report the relative tradeoffs between the different protection schemes in detail. Our results show that our simple heuristic for Streams under online provisioning scenarios offer attractive tradeoffs in terms of blocking, recovery speed, data loss and implementation overhead. We also briefly cover simple ILP solutions to address static offline routing problems, and show that the Streams protection scheme is also efficient under offline routing scenarios as well.